CN111696654A - Hospital bed intelligent distribution method, system, equipment and storage medium - Google Patents
Hospital bed intelligent distribution method, system, equipment and storage medium Download PDFInfo
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- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/20—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
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- G—PHYSICS
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- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
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Abstract
The invention discloses a hospital bed intelligent distribution method, a system, equipment and a storage medium, wherein the method comprises the following steps: acquiring a distribution instruction, and acquiring basic information of a first object according to the distribution instruction; screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence; sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing to obtain a second sequence; assigning the second object to the first object according to the second sequence. The invention realizes the reasonable distribution and the full utilization of hospital bed resources by establishing a bidirectional matching mechanism and distributing according to the real-time conditions of the number of patients and the number of beds.
Description
Technical Field
The invention relates to the field of hospital bed management, in particular to a hospital bed intelligent distribution method, a hospital bed intelligent distribution system, hospital bed intelligent distribution equipment and a hospital bed intelligent distribution storage medium.
Background
Along with the gradual advance of the urbanization process, the density of people living is gradually increased; the problem of allocating medical resources, which is particularly reflected in the field of allocation management of hospital beds, is becoming more prominent. For the distribution of hospital beds, one processing mode is to allocate the bed information and the bed information manually according to the real-time patient information by allocating a professional bed management nurse, and the whole process of the mode is manually guided by people to the distribution process of medical resources, so that the problems of unreasonable distribution and the like are easily caused, even more, the doctor-patient relationship is worsened, and a severe social event is caused; the other mode is to automatically allocate the bed through the system, but in the prior art, the bed is operated by a one-way mechanism, that is, the bed is operated by taking the patient as a main body and matching the patient with the bed, although the reasonable allocation of the bed resources is realized to a certain extent by the mode, the operation by the one-way allocation mechanism has some problems, and when more patients are waiting for the bed and the number of available beds is less, the full utilization of the bed resources cannot be ensured by the mode that the patient matches the bed.
Therefore, how to realize reasonable distribution and full utilization of hospital bed resources by using a bidirectional matching mechanism is a technical problem which is urgently needed to be solved at present.
Disclosure of Invention
In order to solve at least one of the technical problems in the prior art, the invention aims to provide a hospital bed intelligent distribution method, a hospital bed intelligent distribution system, hospital bed intelligent distribution equipment and a hospital bed intelligent distribution storage medium.
According to a first aspect of the embodiment of the invention, the hospital bed intelligent distribution method comprises the following steps:
s100, acquiring a distribution instruction, and obtaining basic information of a first object according to the distribution instruction;
s200, screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence;
s300, sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing to obtain a second sequence;
s400, distributing the second object to the first object according to the second sequence;
in steps S100 to S400, when the first object is a bed, the second object is a patient; when the first object is a patient, the second object is a bed.
Further, when the first object is a bed and the second object is a patient, the step S200 includes:
screening patients meeting the requirements according to the bed information; the bed information comprises at least one of gender information and isolation information;
acquiring and calculating a patient priority score according to patient information of patients meeting requirements; the patient information comprises at least one of selective admission time information, illness state information and system registration time information;
ranking the patients according to the patient priority scores and generating the first sequence.
Further, when the first object is a bed and the second object is a patient, the step S300 includes:
acquiring the treatment type information and the waiting duration information of the patient in sequence according to the first sequence;
obtaining a reception and treatment type weight factor according to the reception and treatment type information, and obtaining a waiting duration weight factor according to the waiting duration information;
calculating the patient matching degree between the patient and the bed according to the patient priority grade, the treatment type weight factor and the waiting duration weight factor;
and sorting the patients according to the patient matching degree and generating the second sequence.
Further, the patient matching degree is calculated by the following formula:
S＝∑(F*SW)*(DW^([(MIN-(D-A))/7]))
wherein S represents the patient match; f represents the patient priority score; SW represents a receiving and treating type weight factor; DW represents a waiting duration weight factor; d represents the current time; a represents the period selection time; MIN represents a preset wait period.
Further, when the first object is a patient and the second object is a bed, the step S200 includes:
screening beds meeting requirements according to the information of the patients; the patient information includes at least one of gender information, isolation information;
acquiring and calculating a bed priority score according to the bed information of the bed meeting the requirements; the bed information comprises at least one of the available bed number and the bed waiting patient number of the ward area where the bed is located;
sorting the beds according to the bed priority scores and generating the first sequence.
Further, when the first object is a bed and the second object is a patient, the step S300 includes:
sequentially acquiring the available bed number and the bed waiting patient number of the ward area where the bed is located according to the first sequence;
obtaining a treatment type weight factor according to the treatment type information of the patient;
calculating the bed matching degree between the bed and the patient according to the bed priority grade score, the available bed number, the number of bed waiting patients and the weight factor of the treatment type;
and sequencing the beds according to the bed matching degree and generating the second sequence.
Further, the bed matching degree is calculated by the following formula:
S＝∑(F*SW)*((A-W)/A)
wherein S represents the bed matching degree; f represents the bed priority score; SW represents a receiving and treating type weight factor; a represents the number of available bed numbers; w represents the number of bed waiting patients.
According to a second aspect of the embodiments of the present invention, an intelligent hospital bed allocation system includes the following modules:
the instruction acquisition module is used for acquiring a distribution instruction and acquiring basic information of the first object according to the distribution instruction; the first subject comprises at least one of a patient, a bed;
the first sequence acquisition module is used for screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence; the second object comprises at least one of a patient and a bed;
the second sequence acquisition module is used for sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing the matching degree to obtain a second sequence;
an assigning module for assigning the second object to the first object according to the second sequence;
wherein when the first object is a bed, the second object is a patient; when the first object is a patient, the second object is a bed.
According to a third aspect of embodiments of the present invention, an apparatus, comprises:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement a method as described in the first aspect.
According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium has stored therein a processor-executable program which, when executed by a processor, is configured to implement the method of the first aspect.
The invention has the beneficial effects that: by establishing a bidirectional matching mechanism, the hospital bed resources are distributed according to the real-time conditions of the number of patients and the number of beds, so that the hospital bed resources are reasonably distributed and fully utilized.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following description is made on the drawings of the embodiments of the present invention or the related technical solutions in the prior art, and it should be understood that the drawings in the following description are only for convenience and clarity of describing some embodiments in the technical solutions of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without creative efforts.
Fig. 1 is a flowchart of an intelligent hospital bed allocation method according to an embodiment of the present invention;
FIG. 2 is a flow chart of an implementation provided by an embodiment of the present invention;
FIG. 3 is a block diagram of a module connection provided by an embodiment of the present invention;
fig. 4 is a connection diagram of a device provided by an embodiment of the present invention.
Detailed Description
The conception, the specific structure and the technical effects of the present invention will be clearly and completely described in conjunction with the embodiments and the accompanying drawings to fully understand the objects, the schemes and the effects of the present invention.
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The terms "first," "second," "third," and "fourth," etc. in the description and claims of the invention and in the accompanying drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the invention. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The embodiment of the invention provides an intelligent hospital bed allocation method, which can be applied to a terminal, a server and software running in the terminal or the server, such as an application program with an image color constancy processing function. The terminal may be, but is not limited to, a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, and the like. The server may be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, or a cloud server providing basic cloud computing services such as cloud service, a cloud database, cloud computing, a cloud function, cloud storage, network service, cloud communication, middleware service, domain name service, security service, CDN, and a big data and artificial intelligence platform. Referring to fig. 1, the method includes the following steps S100-S400:
s100, acquiring a distribution instruction, and obtaining basic information of a first object according to the distribution instruction;
s200, screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence; before screening distributable second objects according to the basic information, firstly checking whether the first object is a specific second object or not, if so, directly distributing the specific second object to the first object; if not, screening to obtain a second assignable object and sequencing;
alternatively, when the first object is a bed and the second object is a patient, the step S200 may be implemented by:
s2011, screening patients meeting requirements according to the bed information; the bed information comprises at least one of gender information and isolation information;
s2012, obtaining and calculating the priority grade of the patient according to the patient information of the patient meeting the requirement; the patient information comprises at least one of selective admission time information, illness state information and system registration time information;
s2013, sorting the patients according to the patient priority scores and generating a first sequence.
Alternatively, when the first object is a patient and the second object is a bed, the step S200 may be implemented by:
s2021, screening beds meeting requirements according to the patient information; the patient information includes at least one of gender information, isolation information;
s2022, obtaining and calculating a bed priority score according to the bed information of the bed meeting the requirements; the bed information comprises at least one of the available bed number and the bed waiting patient number of the ward area where the bed is located;
s2023, sorting the beds according to the bed priority scores and generating a first sequence.
S300, sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing to obtain a second sequence;
alternatively, when the first object is a bed and the second object is a patient, the step S300 may be implemented by:
s3011, acquiring treatment type information and waiting duration information of a patient in sequence according to the first sequence;
s3012, obtaining a reception and treatment type weight factor according to the reception and treatment type information, and obtaining a waiting duration weight factor according to the waiting duration information;
s3013, calculating the matching degree between the patient and the bed according to the priority rating of the patient, the treatment type weight factor and the waiting duration weight factor;
and S3014, sequencing the patients according to the patient matching degree and generating a second sequence.
Alternatively, when the first object is a patient and the second object is a bed, the step S300 may be implemented by:
s3021, sequentially obtaining the number of available beds and the number of bed-waiting patients in a ward where the bed is located according to the first sequence;
s3022, obtaining a treatment type weight factor according to the treatment type information of the patient;
s3023, calculating the matching degree between the bed and the patient according to the priority grade of the bed, the available number of beds, the number of patients waiting for the bed and the weight factor of the treatment type;
and S3024, sequencing the beds according to the matching degree and generating a second sequence.
And S400, distributing the second object to the first object according to the second sequence.
In steps S100 to S400, when the first object is a bed, the second object is a patient; when the first object is a patient, the second object is a bed.
The patient matching degree is mainly calculated by formula (1):
S＝∑(F*SW)*(DW^([(MIN-(D-A))/7])) (1)
wherein S is the patient' S match score; f is the priority score of the patient; SW is a patient's treatment type weighting factor, for example: in some embodiments, SW in the disease area is set to 1, SW in the department is set to 0.9, and SW in the department is set to 0.8; DW is a waiting duration weight factor; d is the current time; a is period selection time; (D-A) is the waiting time of the patient; MIN is a preset wait duration, for example: in some embodiments, we set DW to 0.9, MIN to-13, and calculate for one week, then when: results are 1 when the value is-13 to-8; -7 to-1, resulting in 1 x 0.9; 0 to 6, the result is 1 × 0.9; 7-13, the result is 1 × 0.9.
The bed matching degree is mainly calculated by the formula (2):
S＝∑(F*SW)*((A-W)/A)) (2)
wherein S is the matching degree of the bed; f is the priority score of the bed; SW is a patient's treatment type weighting factor, for example: in some embodiments, SW in the disease area is set to 1, SW in the department is set to 0.9, and SW in the department is set to 0.8; a is the number of available beds; w is the number of patients waiting for bed.
Referring to fig. 2, there is shown an execution flow chart provided according to an embodiment of the present invention, starting allocation; checking basic information of a patient to be allocated or admitted;
if the bed to be matched is the bed, checking whether the bed has patient reservation, if so, returning the patient information to the system and distributing; if not, screening the patients receivable in the bed; calculating and ranking a patient priority score; calculating the matching degree of the patients and sequencing; selecting the most suitable patient according to the sorting result; the allocation is ended.
If the patient to be matched is the patient, checking whether the patient has a reserved bed, if so, returning the bed information by the system and distributing; if not, screening the ward where the patient can live; calculating and sequencing the priority scores of the available beds in the ward; obtaining available bed information in a ward, calculating bed matching degree and sequencing; selecting the most suitable bed according to the sorting result; the allocation is ended.
The bidirectional matching mechanism can be switched to use or used simultaneously according to the real-time environment of a hospital, generally, when a large number of patients to be admitted are present, the patients are selected by taking the bed as the main body, so that the patients most needing medical resources are guaranteed to preferentially enter, and the principle of reasonable allocation of social resources is met; when the existing hospital has a plurality of beds, the patient is taken as the main body to select the bed, so that the patient can be treated in hospital in the environment most suitable for the state of illness of the patient, and the health of the patient can be recovered.
Referring to fig. 3, the present invention also provides an intelligent hospital bed distribution system, which includes the following modules:
the instruction obtaining module 301 is configured to obtain a distribution instruction, and obtain basic information of the first object according to the distribution instruction; the first object comprises at least one of a patient, a bed;
the first sequence acquisition module 302 is connected with the instruction acquisition module 301 to realize interaction, and is used for screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence; the second object comprises at least one of a patient and a bed;
the second sequence acquisition module 303 is connected with the first sequence acquisition module 302 to realize interaction, and is used for sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing the second object and the first object to obtain a second sequence;
and the allocating module 304 is connected with the second sequence acquiring module 303 to realize interaction, and is configured to allocate the second object to the first object according to the second sequence.
Wherein when the first object is a bed, the second object is a patient; when the first object is a patient, the second object is a bed.
Referring to fig. 4, the present invention also provides an apparatus comprising:
at least one processor 401;
at least one memory 402 for storing at least one program;
when the at least one program is executed by the at least one processor 401, the at least one processor 401 is caused to perform the method as shown in fig. 1.
The contents in the method embodiment shown in fig. 1 are all applicable to the embodiment of the system, the functions specifically implemented by the embodiment of the apparatus are the same as those in the method embodiment shown in fig. 1, and the obtained beneficial effects are also the same as those in the method embodiment shown in fig. 1.
The present invention also provides a computer readable storage medium in which a processor-executable program is stored, which, when executed by a processor, is adapted to implement the method as shown in fig. 1.
The contents in the method embodiment shown in fig. 1 are all applicable to the present storage medium embodiment, the functions implemented by the present storage medium embodiment are the same as those in the method embodiment shown in fig. 1, and the advantageous effects achieved by the present storage medium embodiment are also the same as those achieved by the method embodiment shown in fig. 1.
It will be understood that all or some of the steps, systems of methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art.
The embodiments of the present application have been described in detail with reference to the drawings, but the present application is not limited to the embodiments, and various changes can be made without departing from the spirit of the present application within the knowledge of those skilled in the art.
Claims (10)
1. An intelligent hospital bed allocation method is characterized by comprising the following steps:
s100, acquiring a distribution instruction, and obtaining basic information of a first object according to the distribution instruction;
s200, screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence;
s300, sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing to obtain a second sequence;
s400, distributing the second object to the first object according to the second sequence;
in steps S100 to S400, when the first object is a bed, the second object is a patient; when the first object is a patient, the second object is a bed.
2. The hospital bed intelligent distribution method according to claim 1, wherein when the first object is a bed and the second object is a patient, the step S200 includes:
screening patients meeting the requirements according to the bed information; the bed information comprises at least one of gender information and isolation information;
acquiring and calculating a patient priority score according to patient information of patients meeting requirements; the patient information comprises at least one of selective admission time information, illness state information and system registration time information;
ranking the patients according to the patient priority scores and generating the first sequence.
3. The hospital bed intelligent distribution method according to claim 1, wherein when the first object is a bed and the second object is a patient, the step S300 includes:
acquiring the treatment type information and the waiting duration information of the patient in sequence according to the first sequence;
obtaining a reception and treatment type weight factor according to the reception and treatment type information, and obtaining a waiting duration weight factor according to the waiting duration information;
calculating the patient matching degree between the patient and the bed according to the patient priority grade, the treatment type weight factor and the waiting duration weight factor;
and sorting the patients according to the patient matching degree and generating the second sequence.
4. The hospital bed intelligent distribution method according to claim 3, wherein the patient matching degree is calculated by the following formula:
S＝∑(F*SW)*(DW^([(MIN-(D-A))/7]))
wherein S represents the patient match; f represents the patient priority score; SW represents a receiving and treating type weight factor; DW represents a waiting duration weight factor; d represents the current time; a represents the period selection time; MIN represents a preset wait period.
5. The hospital bed intelligent distribution method according to claim 1, wherein when the first object is a patient and the second object is a bed, the step S200 includes:
screening beds meeting requirements according to the information of the patients; the patient information includes at least one of gender information, isolation information;
acquiring and calculating a bed priority score according to the bed information of the bed meeting the requirements; the bed information comprises at least one of the available bed number and the bed waiting patient number of the ward area where the bed is located;
sorting the beds according to the bed priority scores and generating the first sequence.
6. The hospital bed intelligent distribution method according to claim 1, wherein when the first object is a bed and the second object is a patient, the step S300 includes:
sequentially acquiring the available bed number and the bed waiting patient number of the ward area where the bed is located according to the first sequence;
obtaining a treatment type weight factor according to the treatment type information of the patient;
calculating the bed matching degree between the bed and the patient according to the bed priority grade score, the available bed number, the number of bed waiting patients and the weight factor of the treatment type;
and sequencing the beds according to the bed matching degree and generating the second sequence.
7. The hospital bed intelligent distribution method according to claim 6, wherein the bed matching degree is calculated by the following formula:
S＝∑(F*SW)*((A-W)/A)
wherein S represents the bed matching degree; f represents the bed priority score; SW represents a receiving and treating type weight factor; a represents the number of available bed numbers; w represents the number of bed waiting patients.
8. The hospital bed intelligent distribution system is characterized by comprising the following modules:
the instruction acquisition module is used for acquiring a distribution instruction and acquiring basic information of the first object according to the distribution instruction; the first subject comprises at least one of a patient, a bed;
the first sequence acquisition module is used for screening distributable second objects according to the basic information and sequencing the second objects to obtain a first sequence; the second object comprises at least one of a patient and a bed;
the second sequence acquisition module is used for sequentially calculating the matching degree between the second object and the first object according to the first sequence and sequencing the matching degree to obtain a second sequence;
an assigning module for assigning the second object to the first object according to the second sequence;
wherein when the first object is a bed, the second object is a patient; when the first object is a patient, the second object is a bed.
9. An apparatus, comprising:
at least one processor;
at least one memory for storing at least one program;
when executed by the at least one processor, cause the at least one processor to implement the method of any one of claims 1-7.
10. A computer-readable storage medium, in which a program executable by a processor is stored, characterized in that the program executable by the processor is adapted to implement the method according to any one of claims 1-7 when executed by the processor.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113870987A (en) * | 2021-10-20 | 2021-12-31 | 南京润海科星物联网智能科技有限公司 | Use method of medical intelligent bed cabinet |
| CN114283932A (en) * | 2022-03-03 | 2022-04-05 | 四川大学华西医院 | Medical resource management method, device, electronic equipment and storage medium |
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| CN110491489A (en) * | 2019-07-10 | 2019-11-22 | 厦门安盟网络股份有限公司 | Bed recommended method, medium, equipment and system in hospital |
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| CN113870987A (en) * | 2021-10-20 | 2021-12-31 | 南京润海科星物联网智能科技有限公司 | Use method of medical intelligent bed cabinet |
| CN114283932A (en) * | 2022-03-03 | 2022-04-05 | 四川大学华西医院 | Medical resource management method, device, electronic equipment and storage medium |
| CN114283932B (en) * | 2022-03-03 | 2022-06-10 | 四川大学华西医院 | Medical resource management method, device, electronic equipment and storage medium |
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Denomination of invention: A method, system, equipment, and storage medium for intelligent allocation of hospital beds Effective date of registration: 20231206 Granted publication date: 20230919 Pledgee: Bank of China Limited by Share Ltd. Guangzhou Haizhu branch Pledgor: Guangdong Baihui Technology Co.,Ltd. Registration number: Y2023980069624 |