CN117854671A - Method and system for rapidly calculating execution times of first-day or last-day orders - Google Patents
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Abstract
The invention provides a method and a system for rapidly calculating the execution times of first-day or last-day orders, which are characterized in that the execution times of the first-day orders are obtained by extracting the execution frequency codes of the orders from the orders or prescriptions, extracting the total execution times of the orders and specific time points of the orders in a rule index of an ES search server according to the execution frequency codes of the orders, disassembling the specific time points of the orders by a split method, storing the specific time points into a time point array, calculating the length of the array after the start time of the first-day orders to obtain the execution times of the first-day orders, calculating the length of the array before the stop time of the last-day orders to obtain the execution times of the last-day orders, storing the result into a Redis database and checking the abnormal condition of the length of the array; the method and the device accelerate the rule query speed of the calculation of the first order execution times and the last order execution times, avoid repeated calculation of the rules in the same minute section, and solve the problem of high concurrence bottleneck caused by the calculation of the times under the high-frequency order opening operation and the time consumption and error problem of the manual calculation times under the traditional mode.
Description
Technical Field
The invention relates to the technical field of medical services, in particular to a method and a system for rapidly calculating the execution times of first-day or last-day orders.
Background
Along with the increasing perfection of informatization construction of hospitals, the use experience requirement of a user on a clinical system is higher and higher, at present, doctors often need to manually input first-day orders and last-day orders, after inputting the orders, the orders or prescriptions are sent to nurses for checking applications, the first-day orders and last-day orders are calculated in such a way that the operation is complicated, the use experience of doctors and nurses on the clinical system is influenced, the nurses spend a great deal of energy on checking the orders or prescriptions, the orders and repeating withdrawal, and meanwhile, the doctor cannot effectively guarantee the accuracy of the manually input first-day orders and last-day orders and is easy to be wrong; in addition, if the last order execution times are not automatically calculated according to the order stop execution time when the execution of the orders is stopped, the situation that the application fee of medicines or diagnosis is increased and unnecessary losses are caused to patients and hospitals can be caused.
Therefore, in order to solve the above-mentioned problem, the present invention proposes a method and a system for rapidly calculating the number of executions of a first-day or last-day medical order.
Disclosure of Invention
The present invention proposes the following technical solution to one or more of the above technical drawbacks of the prior art.
A method for rapidly calculating the number of first-day or last-day order executions, comprising:
s1, extracting an order execution frequency code, a first order start execution time and a last order stop execution time from orders or prescriptions of a doctor workstation by using an HIS medical information system service, and extracting corresponding total order execution times and specific order execution time points from a rule index of an ES search server according to the order execution frequency code;
s2, disassembling the specific time point of the medical advice execution by using a split method, storing the time point into a time point array, traversing the time point array, and dividing the time point array into an array before the first medical advice execution time and an array after the first medical advice execution time by taking the first medical advice execution time in the medical advice or prescription as a base line; the method comprises the steps of,
dividing the time point component into an array before the last order stop execution time and an array after the last order stop execution time by taking the last order stop execution time in the order or the prescription as a base line;
s3, calculating the length of the array after the first order starts execution time to obtain the first order execution times and calculating the length of the array before the first order starts execution time; the method comprises the steps of,
calculating the length of the array before the execution stopping time of the last order to obtain the execution times of the last order and calculating the length of the array after the execution stopping time of the last order;
and S4, storing the first order execution times and the last order execution times into a related data table of a Redis database, and displaying the first order execution times and the last order execution times in a service front-end page of the HIS medical information system.
According to the calculation method, the problem of actual traditional Chinese medicine order execution times is synchronously resolved into necessary calculated parameters, such as specific time points of order execution, starting execution time of the first order and stopping execution time of the last order, the problem of actual traditional Chinese medicine order execution times is converted into array length to be solved, the array length is used as one of the verification standards of a later calculation method, the first order execution times and the last order execution times can be obtained rapidly, meanwhile, regular maintenance and calibration can be further conducted to ensure that the first order execution times and the last order execution times are scientific and reasonable, orders made by medical staff can be guaranteed to be safely and effectively treated by correctly executing the orders, and meanwhile, the medical staff does not need to consume a great amount of time and energy to check the orders, so that unnecessary loss caused to patients and hospitals is effectively reduced.
Further, the first order execution times are stored in a Redis database in a Key-Value structure, wherein Key is 'order execution frequency code+minutes corresponding to first order start execution time', value is a String type, and represents the corresponding first order execution times.
Further, the last order execution times are stored in a Redis database in a Key-Value structure, wherein Key is 'order execution frequency code+number of minutes corresponding to last order stop execution time', value is a String type and represents the corresponding last order execution times.
The first order execution times and the last order execution times are stored in the Redis database, so that the results of the same frequency and same minute codes are conveniently multiplexed, regular repeated calculation in the same minute section is avoided, the calculation speed is further increased, and the calculation time consumption of the first order execution times and the last order execution times is reduced.
Further, after the number of execution times of the first order and the number of execution times of the last order are calculated, an abnormal condition check is required to be performed on the length of the array, specifically, the sum of the length of the array before the start of the execution time of the first order and the length of the array after the start of the execution time of the first order and the sum of the length of the array before the stop of the execution time of the last order and the length of the array after the stop of the execution time of the last order are calculated;
if the sum of the length of the array before the first order starts execution time and the length of the array after the first order starts execution time is not equal to the total number of times of the order execution, or the sum of the length of the array before the last order stops execution time and the length of the array after the last order stops execution time is not equal to the total number of times of the order execution, checking whether initial rule configuration is wrong, if the initial rule configuration is wrong, timely correcting, and if the initial rule configuration is wrong, performing abnormal registration and performing manual intervention.
Further, the rule index in the ES search server and the data stored in the dis database need to be compared periodically to further determine whether the values stored in the database are reasonable, whether there is a critical time anomaly, and an allocation rule conflict.
The calculation method is calibrated and checked continuously by using a timing strategy, unreasonable factors can be eliminated, so that the calculation method is more intelligent and has more rationality and accuracy.
Based on the second aspect of the invention, a system for rapidly calculating the execution times of first-day or last-day orders is also provided, which comprises an ES search server, a Redis database, a doctor workstation and an HIS medical information system service; wherein,
the ES search server is configured to define a rule among a frequency code of orders, a total number of times of order execution and specific time points of order execution to form a rule index, the doctor workstation is used for order or prescription making operation, the HIS medical information system service is configured to receive orders or prescriptions of the doctor workstation and calculate and obtain a first order execution number and a last order execution number, and the Redis database is used for storing the first order execution number and the last order execution number; in particular, the method comprises the steps of,
the HIS medical information system service acquires the orders or prescriptions of the doctor workstation, synchronously decomposes the order execution frequency codes, the total times of order execution and rule data among specific time points of the order execution, and automatically inserts the rule data into the ES search server structure index to form a rule index;
the HIS medical information system service receives the medical advice or prescription setting information, extracts the corresponding total times of medical advice execution and the corresponding specific time points of medical advice execution from the rule index according to the medical advice execution frequency code, calculates the first-day medical advice execution times or the last-day medical advice execution times according to the method for calculating the first-day medical advice execution times or the last-day medical advice execution times, stores the first-day medical advice execution times and the last-day medical advice execution times into a related data table of the Redis database in a Key-Value structure, and displays the first-day medical advice execution times and the last-day medical advice execution times in a service front-end page of the HIS medical information system.
Through the related technologies of the ES search server and the Redis database, the first order execution times and the last order execution times are rapidly calculated, and the problems of more time consumption and large error caused by manual calculation in a traditional mode and the high concurrency bottleneck problem caused by high-frequency single-opening operation calculation are solved.
Further, when a doctor issues a bill to generate a new medical order or prescription, judging whether a Key of the first medical order execution times or a Key of the last medical order execution times exists in the Redis database;
if yes, extracting the Key of the first order execution times or the Key of the last order execution times, and obtaining the first order execution times or the last order execution times according to the Value corresponding to the Key of the first order execution times or the Key of the last order execution times;
and if the number of the first order execution times or the last order execution times is not calculated, extracting an order execution specific time point and an order execution total number corresponding to the order execution frequency code from the ES search server, and then calculating according to any one of the methods for calculating the first order execution times or the last order execution times to obtain new first order execution times or new last order execution times and updating the new first order execution times or the new last order execution times into a data table corresponding to a Redis database.
The first order execution times and the last order execution times are correctly generated by combining the first order start execution time and the last order stop execution time, so that the efficiency of operating and making orders and stopping executing orders by clinical medical staff is improved, unnecessary medicine withdrawal work and the problem of incorrect inputting of the clinical medical staff are also reduced, and doctor-patient disputes are also reduced to a certain extent.
Based on a third aspect of the present invention, there is also provided a computer-readable storage medium having stored thereon one or more computer programs which, when executed by a computer processor, implement a method as described in any of the above.
The invention has the technical effects that: the method has the advantages that the rule query speed of the calculation of the first order execution times and the last order execution times is quickened, repeated calculation of the same-minute-period rule is avoided, and the problem of high concurrence bottleneck caused by the calculation of the times under high-frequency order opening operation and the time consumption and error problem of manual calculation times under the traditional mode are solved.
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Other features, objects and advantages of the present application will become more apparent upon reading of the detailed description of non-limiting embodiments made with reference to the following drawings.
FIG. 1 is a general flow chart of a method for quickly calculating the number of first or last order executions provided in accordance with an embodiment of the present invention.
FIG. 2 is a block diagram of a system for quickly calculating the number of first or last order executions provided in accordance with an embodiment of the present invention.
Fig. 3 is a schematic diagram of a computer system suitable for use in implementing embodiments of the present application.
Detailed Description
The present application is described in further detail below with reference to the drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be noted that, for convenience of description, only the portions related to the present invention are shown in the drawings.
It should be noted that, in the case of no conflict, the embodiments and features in the embodiments may be combined with each other. The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.
FIG. 1 illustrates a general flow chart of a method for quickly calculating the number of first or last order executions, including:
s1, extracting an order execution frequency code, a first order start execution time and a last order stop execution time from orders or prescriptions of a doctor workstation by using an HIS medical information system service, and extracting corresponding total order execution times and specific order execution time points from a rule index of an ES search server according to the order execution frequency code;
s2, disassembling the specific time point of the medical advice execution by using a split method, storing the time point into a time point array, traversing the time point array, and dividing the time point array into an array before the first medical advice execution time and an array after the first medical advice execution time by taking the first medical advice execution time in the medical advice or prescription as a base line; the method comprises the steps of,
dividing the time point component into an array before the last order stop execution time and an array after the last order stop execution time by taking the last order stop execution time in the order or the prescription as a base line;
s3, calculating the length of the array after the first order starts execution time to obtain the first order execution times and calculating the length of the array before the first order starts execution time; the method comprises the steps of,
calculating the length of the array before the execution stopping time of the last order to obtain the execution times of the last order and calculating the length of the array after the execution stopping time of the last order;
and S4, storing the first order execution times and the last order execution times into a related data table of a Redis database, and displaying the first order execution times and the last order execution times in a service front-end page of the HIS medical information system.
The ES search server is a distributed open source search engine, stores data in a non-relational database mode, supports near-real-time search and near-real-time document update, and has the advantages of high instantaneity and good expansibility.
It should be noted that the Redis database has extremely high read-write speed, and has a more complex data structure than other databases, and all operations are atomic and support data persistence.
The first order execution times are stored in a Redis database in a Key-Value structure, wherein Key is ' order execution frequency code+minutes corresponding to first order start execution time ', value is a String type and represents corresponding first order execution times '.
It should be noted that, the last order execution times are stored in the Redis database in a Key-Value structure, where Key is "the order execution frequency code+the number of minutes corresponding to the last order stop execution time", and Value is a String type, and represents the corresponding last order execution times.
In a specific embodiment, the ES search service stores an initialization rule corresponding to the order execution frequency code in a Key-Value structure, where Key is the order execution frequency code, and Value is the total number of times of order execution or a specific time point list of order execution.
It should be noted that, after the number of execution times of the first order and the number of execution times of the last order are calculated, it is also necessary to perform an abnormal condition check on the length of the array, specifically, calculate the sum of the length of the array before the execution time of the first order and the length of the array after the execution time of the first order, and the sum of the length of the array before the execution time of the last order and the length of the array after the execution time of the last order;
if the sum of the length of the array before the first order starts execution time and the length of the array after the first order starts execution time is not equal to the total number of times of the order execution, or the sum of the length of the array before the last order stops execution time and the length of the array after the last order stops execution time is not equal to the total number of times of the order execution, checking whether initial rule configuration is wrong, if the initial rule configuration is wrong, timely correcting, and if the initial rule configuration is wrong, performing abnormal registration and performing manual intervention.
It should be noted that, if the initial rule is configured with errors, the rule corresponding to the order frequency code is re-split and processed and updated to the index corresponding to the ES search server in time after correction.
In one particular embodiment, the system begins execution time for the first order extracted from the order or prescription at the doctor workstation by the HIS medical information system service as "09:10", extracting the corresponding order execution total times from the rule index of the ES search server according to the order execution frequency code to be 4, which means that the order execution frequency in one day is four times, and similarly, extracting the corresponding order execution specific time point from the rule index of the ES search server according to the order execution frequency code to be 08:00"," 12:00"," 16:00 "and" 20:00";
the system disassembles the medical advice to execute specific time points through a split method and stores the specific time points into a time point array, traverses the time point array, and starts executing time '09' with the first medical advice: 10 "groups time points into arrays {"08 "before the first order start execution time for baseline: 00"}, length 1, and an array after the first order start execution time {"12:00"," 16:00"," 20:00", length is 3, namely, the number of times of the first-day doctor's advice execution;
the sum of the length of the array before the first order starts execution time and the length of the array after the first order starts execution time is 4, which is equal to the total number of times of the order execution, belongs to the normal condition, and if the sum of the length of the array before the first order starts execution time and the length of the array after the first order starts execution time is not equal to the abnormal condition of the total number of times of the order execution, whether the initial rule configuration is wrong needs to be checked, and the initial rule configuration is corrected in time when the error occurs, and if the initial rule configuration is correct, the abnormal registration and the manual intervention are performed.
In one particular embodiment, the system begins execution time for a last order extracted from an order or prescription at a doctor workstation by the HIS medical information system service of "13:20", extracting the corresponding order execution total times from the rule index of the ES search server according to the order execution frequency code to be 3, which means that the order execution frequency in one day is three times, and similarly, extracting the corresponding order execution specific time point from the rule index of the ES search server according to the order execution frequency code to be 08:00"," 12:00 "and" 16: 00';
the system disassembles the doctor's advice to carry out the concrete time point and stores to the time point array through the split method, traverse the time point array, take last doctor's advice stop execution time "13:20" as the base line and divide the time point group into the array { "08" before last doctor's advice stop execution time: 00", 12: 00' }, the length is 2, namely the number of times of stopping execution of the last order, and an array { "16" after the stopping execution time of the last order: 00"}, length 1.
The sum of the length of the array before the last order stop execution time and the length of the array after the last order stop execution time is 3, is equal to the total number of times of the order execution, belongs to the normal condition, and if the sum of the length of the array before the last order stop and the length of the array after the last order stop is not equal to the abnormal condition of the total number of times of the order execution, whether the initial rule configuration is wrong needs to be checked, and the initial rule configuration is corrected in time when the error occurs, and if the initial rule configuration is wrong, the abnormal registration and the manual intervention are carried out.
It should be noted that, if the order start execution time and the order stop execution time in the order or the prescription are in the same day, the length of the order execution specific time point array between the order start execution time and the order stop execution time is the number of times of the order execution on the same day.
It should be noted that, the system program sets a plurality of timing services to trigger at a designated time point, scans the ES search server and the references database, and checks the data rules stored in the ES search server and the data results stored in the references database according to the set check rules, so as to determine whether the determination is accurate.
It should be noted that, the rule index in the ES search server and the data stored in the Redis database need to be compared regularly to further determine whether the values stored in the database are reasonable, whether there is a critical time anomaly and an allocation rule conflict.
In a specific embodiment, the total number of times of executing the orders stored in the server of the ES is 3, and the specific time point of executing the orders is "08:00"," 12:00", 16:00", and "20:00", does not correspond to the total number of order executions, determining that a rule conflict exists; similarly, if the total number of times of execution of the orders stored in the server of the ES is 3, the Redis database determines that the number of times of execution of the first order is 5, and there is also an error.
In a specific embodiment, the specific time point of the order execution set in the ES server is "08:00"," 12:00", 16:00", when the first order start execution time is "08:00", namely the critical time point (set as backward attribution), the calculated first order execution times is 3, if the first order execution times obtained by the Redis database is 2, the critical time abnormality exists.
Referring now to FIG. 2, there is shown a system architecture diagram for rapidly calculating the number of first or last order executions, including an ES search server a, a Redis database b, a doctor workstation c, and a HIS medical information system service d; wherein,
the ES search server is configured to define a rule among a frequency code of orders, a total number of times of order execution and specific time points of order execution to form a rule index, the doctor workstation is used for order or prescription making operation, the HIS medical information system service is configured to receive orders or prescriptions of the doctor workstation and calculate and obtain a first order execution number and a last order execution number, and the Redis database is used for storing the first order execution number and the last order execution number; in particular, the method comprises the steps of,
the HIS medical information system service acquires the orders or prescriptions of the doctor workstation, synchronously decomposes the order execution frequency codes, the total times of order execution and rule data among specific time points of the order execution, and automatically inserts the rule data into the ES search server structure index to form a rule index;
the HIS medical information system service receives the medical advice or prescription setting information, extracts the corresponding total times of medical advice execution and the corresponding specific time points of medical advice execution from the rule index according to the medical advice execution frequency code, calculates the first-day medical advice execution times or the last-day medical advice execution times according to the method for calculating the first-day medical advice execution times or the last-day medical advice execution times, stores the first-day medical advice execution times and the last-day medical advice execution times into a related data table of the Redis database in a Key-Value structure, and displays the first-day medical advice execution times and the last-day medical advice execution times in a service front-end page of the HIS medical information system.
It should be noted that, the method for calculating the first order execution times or the last order execution times includes:
the system extracts the order execution frequency code, the first order start execution time and the last order stop execution time from the orders or prescriptions of the doctor workstation through the HIS medical information system service, and extracts the corresponding total order execution times and specific time points of the order execution from the rule index of the ES search server according to the order execution frequency code;
disassembling the specific time point of the medical advice execution by using a split method, storing the time point into a time point array, traversing the time point array, and dividing the time point array into an array before the first medical advice execution time and an array after the first medical advice execution time by taking the first medical advice execution time in the medical advice or prescription as a base line; the method comprises the steps of,
dividing the time point component into an array before the last order stop execution time and an array after the last order stop execution time by taking the last order stop execution time in the order or the prescription as a base line;
calculating the length of the array after the first order starts execution time to obtain the first order execution times and calculating the length of the array before the first order starts execution time; the method comprises the steps of,
calculating the length of the array before the execution stopping time of the last order to obtain the execution times of the last order and calculating the length of the array after the execution stopping time of the last order;
and storing the first order execution times and the last order execution times into a related data table of a Redis database, and displaying the first order execution times and the last order execution times in a service front-end page of the HIS medical information system.
When a doctor issues a bill to generate a new doctor's advice or prescription, judging whether a Key of the first doctor's advice execution times or a Key of the last doctor's advice execution times exists in the Redis database;
if yes, extracting the Key of the first order execution times or the Key of the last order execution times, and obtaining the first order execution times or the last order execution times according to the Value corresponding to the Key of the first order execution times or the Key of the last order execution times;
and if the number of times of the first order execution or the number of times of the last order execution is not calculated, the new number of times of the first order execution or the new number of times of the last order execution is obtained by re-extracting the specific time point of the order execution and the total number of times of the order execution corresponding to the order execution frequency code from the ES search server, and updating the new number of times of the first order execution or the new number of times of the last order execution into a data table corresponding to a Redis database.
The first order execution times are stored in a Redis database in a Key-Value structure, wherein Key is ' order execution frequency code+minutes corresponding to first order start execution time ', value is a String type and represents corresponding first order execution times '.
It should be noted that, the last order execution times are stored in the Redis database in a Key-Value structure, where Key is "the order execution frequency code+the number of minutes corresponding to the last order stop execution time", and Value is a String type, and represents the corresponding last order execution times.
It should be noted that, after the number of execution times of the first order and the number of execution times of the last order are calculated, it is also necessary to perform an abnormal condition check on the length of the array, specifically, calculate the sum of the length of the array before the execution time of the first order and the length of the array after the execution time of the first order, and the sum of the length of the array before the execution time of the last order and the length of the array after the execution time of the last order;
if the sum of the length of the array before the first order starts execution time and the length of the array after the first order starts execution time is not equal to the total number of times of the order execution, or the sum of the length of the array before the last order stops execution time and the length of the array after the last order stops execution time is not equal to the total number of times of the order execution, checking whether initial rule configuration is wrong, if the initial rule configuration is wrong, timely correcting, and if the initial rule configuration is wrong, performing abnormal registration and performing manual intervention.
It should be noted that, if the order start execution time and the order stop execution time in the order or the prescription are in the same day, the length of the order execution specific time point array between the order start execution time and the order stop execution time is the number of times of the order execution on the same day.
It should be noted that, the rule index in the ES search server and the data stored in the Redis database need to be compared regularly to further determine whether the values stored in the database are reasonable, whether there is a critical time anomaly and an allocation rule conflict.
Referring now to FIG. 3, a schematic diagram of a computer system suitable for use in implementing embodiments of the present application is shown. The electronic device shown in fig. 3 is only an example and should not be construed as limiting the functionality and scope of use of the embodiments herein.
As shown in fig. 3, the computer system includes a Central Processing Unit (CPU) 301 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 302 or a program loaded from a storage section 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data required for the system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other through a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
The following components are connected to the I/O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output portion 307 including a Liquid Crystal Display (LCD) or the like, a speaker or the like; a storage section 308 including a hard disk or the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. The drive 310 is also connected to the I/O interface 305 as needed. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is installed on the drive 310 as needed, so that a computer program read therefrom is installed into the storage section 308 as needed.
In particular, according to embodiments of the present disclosure, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable storage medium, the computer program comprising program code for performing the method shown in the flowcharts. In such an embodiment, the computer program may be downloaded and installed from a network via the communication portion 309, and/or installed from the removable medium 311. The above-described functions defined in the method of the present application are performed when the computer program is executed by a Central Processing Unit (CPU) 301. It should be noted that the computer readable storage medium 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 can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. 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 (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, however, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with computer-readable program code 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 storage 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. Program code embodied on a computer readable storage medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations of the present application may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).
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. In this regard, 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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 modules involved in the embodiments described in the present application may be implemented by software, or may be implemented by hardware.
As another aspect, the present application also provides a computer-readable storage medium that may be included in the electronic device described in the above embodiments; or may exist alone without being incorporated into the electronic device. The computer-readable storage medium carries one or more programs that, when executed by the electronic device, cause the electronic device to: extracting an order execution frequency code, a first order start execution time and a last order stop execution time from orders or prescriptions of a doctor workstation through an HIS medical information system service, and extracting corresponding total order execution times and an order execution specific time point from a rule index of an ES search server according to the order execution frequency code; disassembling the specific time point of the medical advice execution by using a split method, storing the time point into a time point array, traversing the time point array, and dividing the time point array into an array before the first medical advice execution time and an array after the first medical advice execution time by taking the first medical advice execution time in the medical advice or prescription as a base line; and dividing the time point component into an array before the last order stop execution time and an array after the last order stop execution time by taking the last order stop execution time in the order or the prescription as a base line; calculating the length of the array after the first order starts execution time to obtain the first order execution times and calculating the length of the array before the first order starts execution time; calculating the length of the array before the execution stopping time of the last order to obtain the execution times of the last order and calculating the length of the array after the execution stopping time of the last order; and storing the first order execution times and the last order execution times into a related data table of a Redis database, and displaying the first order execution times and the last order execution times in a service front-end page of the HIS medical information system.
Finally, what should be said is: the foregoing description is only of the preferred embodiments of the present application and is presented as a description of the principles of the technology being utilized. It will be appreciated by persons skilled in the art that the scope of the invention referred to in this application is not limited to the specific combinations of features described above, but it is intended to cover other embodiments in which any combination of features described above or equivalents thereof is possible without departing from the spirit of the invention. Such as the above-described features and technical features having similar functions (but not limited to) disclosed in the present application are replaced with each other.
Claims (8)
1. A method for rapidly calculating the execution times of a first-day or last-day doctor's advice, comprising the following steps:
s1, extracting an order execution frequency code, a first order start execution time and a last order stop execution time from orders or prescriptions of a doctor workstation by using an HIS medical information system service, and extracting corresponding total order execution times and specific order execution time points from a rule index of an ES search server according to the order execution frequency code;
s2, disassembling the specific time point of the medical advice execution by using a split method, storing the time point into a time point array, traversing the time point array, and dividing the time point array into an array before the first medical advice execution time and an array after the first medical advice execution time by taking the first medical advice execution time in the medical advice or prescription as a base line; the method comprises the steps of,
dividing the time point component into an array before the last order stop execution time and an array after the last order stop execution time by taking the last order stop execution time in the order or the prescription as a base line;
s3, calculating the length of the array after the first order starts execution time to obtain the first order execution times and calculating the length of the array before the first order starts execution time; the method comprises the steps of,
calculating the length of the array before the execution stopping time of the last order to obtain the execution times of the last order and calculating the length of the array after the execution stopping time of the last order;
and S4, storing the first order execution times and the last order execution times into a related data table of a Redis database, and displaying the first order execution times and the last order execution times in a service front-end page of the HIS medical information system.
2. The method of claim 1, wherein the number of first order executions is stored in a Redis database in a Key-Value structure, where Key is "number of minutes corresponding to the order execution frequency code+the first order start execution time", and Value is a String type, and represents the number of corresponding first order executions.
3. The method of claim 1, wherein the last order execution times are stored in a Redis database in a Key-Value structure, where Key is "order execution frequency code+number of minutes corresponding to last order stop execution time", and Value is a String type, and represents the corresponding last order execution times.
4. The method according to claim 1, wherein an exception check is also required for the length of the array after the calculation of the first order execution times and the last order execution times, in particular, the sum of the length of the array before the first order start execution time and the length of the array after the first order start execution time, and the sum of the length of the array before the last order stop execution time and the length of the array after the last order stop execution time are calculated;
if the sum of the length of the array before the first order starts execution time and the length of the array after the first order starts execution time is not equal to the total number of times of the order execution, or the sum of the length of the array before the last order stops execution time and the length of the array after the last order stops execution time is not equal to the total number of times of the order execution, checking whether initial rule configuration is wrong, if the initial rule configuration is wrong, timely correcting, and if the initial rule configuration is wrong, performing abnormal registration and performing manual intervention.
5. The method of claim 1, wherein the rule index in the ES search server and the data stored in the dis database need to be periodically compared to further determine if the values stored in the database are reasonable, if there is a critical time anomaly, and if there is an allocation rule conflict.
6. A system for rapidly calculating the execution times of first-day or last-day orders comprises an ES search server, a Redis database, a doctor workstation and an HIS medical information system service; wherein,
the ES search server is configured to define a rule among a frequency code of orders, a total number of times of order execution and specific time points of order execution to form a rule index, the doctor workstation is used for order or prescription making operation, the HIS medical information system service is configured to receive orders or prescriptions of the doctor workstation and calculate and obtain a first order execution number and a last order execution number, and the Redis database is used for storing the first order execution number and the last order execution number; in particular, the method comprises the steps of,
the HIS medical information system service acquires the orders or prescriptions of the doctor workstation, synchronously decomposes the order execution frequency codes, the total times of order execution and rule data among specific time points of the order execution, and automatically inserts the rule data into the ES search server structure index to form a rule index;
the HIS medical information system service receives the order or prescription order information, extracts the corresponding total number of times of order execution and the corresponding specific time point of order execution from the rule index according to the order execution frequency code, calculates the first order execution number and the last order execution number according to the method as set forth in any one of claims 1 to 5, stores the first order execution number and the last order execution number in a relevant data table of the Redis database in a Key-Value structure, and displays the first order execution number and the last order execution number in a front page of the HIS medical information system service.
7. The system of claim 6, wherein when a doctor issues a list to generate a new order or prescription, determining whether there is a Key for the first order execution number or a Key for the last order execution number in the Redis database;
if yes, extracting the Key of the first order execution times or the Key of the last order execution times, and obtaining the first order execution times or the last order execution times according to the Value corresponding to the Key of the first order execution times or the Key of the last order execution times;
and if the new first order execution times or the new last order execution times are obtained by carrying out operation according to the method of any one of claims 1-5 and are updated into a data table corresponding to a Redis database.
8. A computer-readable storage medium, having stored thereon one or more computer programs, which when executed by a computer processor, implement the method of any of claims 1-5.
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