CN111370105B - Distributed data storage method and system for hospital logistics management - Google Patents
Distributed data storage method and system for hospital logistics management Download PDFInfo
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Abstract
The invention discloses a distributed data storage method for hospital logistics management, which specifically comprises the following steps: the method comprises the following steps: the acquisition module acquires the logistics information and the attendance information of the hospital and respectively transmits the logistics information and the attendance information to the storage module and the analysis module; step two: the analysis module analyzes and calculates the treatment rate, the use frequency of a sickbed, the disassembly frequency of the sickbed and the use frequency of equipment according to the logistics information and the treatment information, the acquired logistics information and the treatment information are analyzed by the analysis module, so that the abrasion degree of the equipment and the sickbed is calculated, the data of the required equipment and the sickbed are calculated in the pre-purchase calculation module according to the abrasion degree, the diversity of data analysis is realized, the data is classified and analyzed, the analysis time is saved, the accuracy of the data analysis is improved, and the persuasion of the data is improved.
Description
Technical Field
The invention relates to the technical field of data storage, in particular to a distributed data storage method and a distributed data storage system for hospital logistics management.
Background
Hospitals refer to medical institutions that carry out necessary medical examination, treatment measures, nursing techniques, reception services, rehabilitation equipment, treatment and transportation and the like for patients according to laws, regulations and industrial specifications, and mainly aim at saving and killing injuries, the service objects of the medical nursing system not only comprise patients and wounded persons with symptoms, but also comprise old people which cannot take care of themselves or are limited in activity and dependent on medical nursing, severe patients who need long-term rehabilitation and frequent observation and examination due to medical nursing dependence or unstable illness state, or there may be other specific situations and groups of people, such as healthy people and fully healthy people, that, when initially set up, is used for people to take refuge, is provided with entertainment programs, makes the coming people comfortable, has the intention of hospitalization, and then gradually becomes a special mechanism for accommodating and treating patients, behind the facility there is a logistics management system supporting the operation of the facility in the hospital.
A method and system for determining the operational status of a large data storage system is disclosed in prior patent publication No. CN109271104A, the method and the system for determining the operating state of the big data storage system solve the problem that in the current big data storage system, as the number of low frequency data items (data items that are accessed less frequently) becomes greater and greater over time, this typically leads to a problem of reduced data access efficiency for large data storage systems, however, the method and the system for determining the operating state of the big data storage system cannot accurately analyze the logistics management data of the hospital and store the data information in a classified manner according to the accurate analysis result, and simultaneously, while data storage is carried out, the demand quantity of relevant equipment of a hospital cannot be automatically calculated, and therefore a distributed data storage method and a distributed data storage system for hospital logistics management are provided.
Disclosure of Invention
The invention aims to provide a distributed data storage method and a system for hospital logistics management, which accurately analyze relevant logistics information and treatment information through the arrangement of an acquisition module, an analysis module and a pre-purchase calculation module, so that the diversity of data analysis is realized, the data is classified and analyzed, the analysis time is saved, the accuracy of data analysis is increased, the persuasion of the data is increased, the data information is classified and stored through the arrangement of a treatment data unit, a sickbed data unit, an equipment data unit and a demand data unit in a storage module, the data can be conveniently and quickly searched by workers, the search time is saved, the complaint calculation is automatically carried out on hospital equipment, the sufficiency of hospital equipment is ensured, the artificial calculation time is saved, the phenomenon of insufficient equipment is avoided, and the working efficiency is improved.
The technical problem to be solved by the invention is as follows:
(1) how to analyze the acquired logistics information and the acquired clinic information through the analysis module so as to calculate the clinic visiting rate, the sickbed using frequency, the sickbed disassembling frequency and the equipment using frequency, calculate the abrasion degree of the equipment and the sickbed according to the analysis module, calculate the data of the required equipment and the sickbed in the pre-purchasing calculation module according to the abrasion degree, and solve the problem that the data cannot be accurately analyzed in the prior art;
(2) how to classify logistics information, treatment information, abrasion degrees of equipment and sickbeds, quantity data of required sickbeds and equipment, treatment rate, sickbed use frequency, sickbed disassembly frequency and equipment use frequency through the arrangement of the storage module, and the treatment data unit, the sickbed data unit, the equipment data unit and the demand data unit which correspond to the storage values are stored respectively, so that the problem that equipment preparation amount cannot be automatically analyzed while storage in the prior art is solved.
The purpose of the invention can be realized by the following technical scheme: a distributed data storage method for hospital logistics management specifically comprises the following steps:
the method comprises the following steps: the acquisition module acquires the logistics information and the attendance information of the hospital and respectively transmits the logistics information and the attendance information to the storage module and the analysis module;
step two: the analysis module analyzes and calculates the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency according to the logistics information and the treatment information, calculates the abrasion degree of the equipment and the sickbed according to the abrasion degree, and transmits the abrasion degree calculation results of the equipment and the sickbed to the pre-purchase calculation module;
step three: the pre-purchase calculation module calculates the estimated durable time of each sickbed and equipment according to the abrasion degree calculation results of the equipment and the sickbed, the using time data of each sickbed and the using time data of each equipment, carries out durable time safety judgment on the sickbed and the equipment according to the estimated durable time, calculates the quantity data of the needed sickbed and equipment according to the durable time safety judgment results of the sickbed and the equipment and the residual quantity data of the sickbed and the equipment in the database, and transmits the quantity data to the storage module;
step four: the storage module carries out classified storage according to the logistics information and the treatment information acquired by the acquisition module, the equipment and sickbed abrasion degree calculation results analyzed by the analysis module and the pre-purchase calculation module, the required sickbed and equipment quantity data, the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency, and sends a storage success reminding signal to the intelligent equipment after the storage is finished;
step five: and after receiving the storage success reminding signal, the intelligent equipment reminds the user to carry out storage checking.
A distributed data storage system for hospital logistics management comprises an acquisition module, an analysis module, a database, a pre-purchase calculation module, a storage module and intelligent equipment;
the system comprises a collection module, a storage module and an analysis module, wherein the collection module is used for collecting the logistics information and the treatment information of a hospital, the treatment information comprises treatment time data, treatment number data and hospitalization number data, and the logistics information comprises sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data which are respectively transmitted to the storage module and the analysis module;
the analysis module is used for analyzing and operating the visit time data, the visit number data, the number of hospitalized patients, the sickbed use time data, the sickbed disassembly time data, the equipment use time data, the equipment highest temperature data and the patient weight data to obtain the abrasion degree of the sickbed and the abrasion degree of the equipment, and transmitting the abrasion degree of the sickbed and the abrasion degree of the equipment to the pre-purchase calculation module;
the database stores the remaining data of the sickbed and the remaining data of the equipment, and the pre-purchase calculation module is used for performing pre-purchase calculation operation on the abrasion degree of the sickbed and the abrasion degree of the equipment to obtain the quantity of the sickbed which is urgently needed to be increased and the quantity of the equipment which is urgently needed to be increased and transmitting the quantity of the sickbed which is urgently needed to be increased and the quantity of the equipment which is urgently needed to be;
the storage module comprises a hospital data unit, a hospital bed data unit, an equipment data unit and a demand data unit, and the storage module is used for performing distributed storage on the emergency demand of increasing the number of sickbeds, the emergency demand of increasing the number of equipment, the hospital time data, the hospital number data, the hospital bed use time data, the hospital bed disassembly time data, the equipment use time data, the equipment maximum temperature data and the patient weight data, the hospital frequency, the hospital bed use frequency, the hospital bed disassembly frequency, the equipment use frequency, the abrasion degree of the hospital bed and the abrasion degree of the equipment, and specifically comprises the following steps: the hospital information storage system comprises a hospital information storage unit, a hospital information storage unit and a hospital information.
And after receiving the storage success reminding signal, the intelligent equipment reminds the user to carry out storage checking.
As a further improvement of the invention: the specific operation process of the analysis operation is as follows:
k1: acquiring visit time data, visit number data, hospitalization number data, sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data, sequentially marking the data as JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi, wherein i is 1, 2, 3....... n1, and the JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi correspond one to one;
k2: acquiring the number data of the visitors in a period of time, marking the number data of the visitors at JR1 and JR2, marking the corresponding time data of the visitors as JS1 and JS2, and bringing the data of the visitors together into a calculation formula:
wherein, VThen is turned onExpressed as frequency of visit, PJSJS2-JS1, which represents the number of visits within a certain visit time data, PJRJR2-JR1, expressed as total time within a certain visit time data;
k3: acquiring the number data of the hospitalized people, and bringing the number data of the hospitalized people and the corresponding number data of the visiting people into a calculation formula: the sickbed use frequency data and the corresponding sickbed use time data are brought into a calculation formula together: vBedBCi/BSi, where VBedThe frequency of use of the patient bed is represented, and the patient bed disassembly time data are brought into a calculation formula together: vDisassemblingCXi/CSi, wherein VDisassemblingAnd (3) expressing the sickbed detachment frequency, and bringing the data of the use times of the equipment and the data of the use time of the equipment into a calculation formula together: vIs provided withSCi/SSi, wherein VIs provided withExpressed as the frequency of use of the device;
k4: acquiring the daily highest temperature data of the equipment in a period of time, setting a temperature preset value M, and bringing the temperature preset value M and the highest temperature data of the equipment into a calculation formula: pIs provided with＝VIs provided with*[(SWi-M)*u1+M*u2]Wherein P isIs provided withAnd (3) expressed as the wear degree of the equipment, u1 expressed as the wear coefficient exceeding the preset temperature, u2 expressed as the wear coefficient within the preset temperature range, setting a preset value of the weight of the patient, acquiring the sickbed disassembly frequency, the sickbed use frequency and the weight data of the patient in the K3, and bringing the data and the preset value of the weight of the patient into a calculation formula: pBed＝VDisassembling*u3+VBedU4+ (BTi-m) u5+ m u6, wherein PBedThe wear degree of the sickbed is represented, u3 is a wear coefficient of the sickbed caused by the frequency of sickbed disassembly, u4 is a wear coefficient of the sickbed caused by the frequency of sickbed use, u5 is a wear coefficient of the sickbed caused by damage when a weight preset value is exceeded, u6 is a wear coefficient of the sickbed caused by damage within a weight preset value range, m is a patient weight preset value, and a period of time is defined as the day one of the previous month to the last day of the previous month.
As a further improvement of the invention: the specific operation process of the pre-purchase calculation operation comprises the following steps:
c1: acquiring the service time data BSi of each sickbed and the wear degree P of each sickbedBedAnd brings them together into the calculation:
wherein, VWear and tearExpressed as the wear rate of the bed in use, a maximum value of the bed wear is set and is brought into the calculation formula together with the bed wear rate:
wherein, TPreparation ofThe data is expressed as the predicted available time of the sickbed, and F1 is expressed as a preset value of the maximum value of the abrasion degree of the sickbed;
c2: acquiring the service time data SSi of each device and the wear degree P of the deviceIs provided withAnd brings them together into the calculation: vSet of damage＝PIs provided with/SSi, wherein VSet of damageExpressed as the wear rate of the equipment in use, a maximum value of the wear level of the equipment is set and is entered into the calculation equation together with the wear rate of the equipment:
wherein S isPreparation ofExpressing the predicted available time data of the equipment, and F2 expressing the preset value of the maximum value of the wear degree of the equipment;
c3: obtaining a predicted time of use T for each bed and each devicePreparation ofAnd SPreparation ofSetting preset safe use time values A1 and A2 of the sickbed and the equipment respectively, and comparing the preset safe use time values with the expected use time of each sickbed and each equipment to obtain a difference value CT between the expected use time values and the preset safe use time values of the sickbed and the equipmentPreparation ofAnd CSPreparation of；
C4: setting a difference preset value B1 and B2 of the sickbed and the equipment respectively, and comparing the difference CT with the preset value of the predicted use time and the safe use time of the sickbed and the equipment in the C3Preparation ofAnd CSPreparation ofAnd (3) carrying out comparison, wherein the specific comparison result is as follows: aiming at a sickbed: when C is presentTPreparation ofWhen the time is less than or equal to B1, the patient bed is judged to have short service life and needs to be replaced in time, a patient bed replacement signal is generated, and when CT is carried outPreparation ofWhen the length of the life time of the sickbed is greater than B1, the sickbed is judged to have long service life, the sickbed can be continuously used, a sickbed warning signal is generated, and the life time of the sickbed is determined according to the following conditions: when CS is usedPreparation ofWhen the time is B2 or less, the device is judged to have a short service life and to be replaced in time, a device replacement signal is generated, and when CS is usedPreparation ofIf the length is more than B2, judging that the duration of the sickbed is long, and generating an equipment warning signal by continuously using the sickbed;
c5: the times of occurrence of the sickbed replacement signal, the sickbed warning signal, the equipment replacement signal and the equipment warning signal are extracted and marked as E1, E2, E3 and E4, and are compared with sickbed residual data and equipment residual data in a database, and the method specifically comprises the following steps:
h1: using the calculation: g1 ═ E1+ E2 × v1-L1, and the amount of the patient beds which need to be increased is calculated, wherein G1 represents the number of the patient beds which need to be increased, v1 represents an image factor of the damage of the patient beds when the patient bed warning signal occurs, and L1 represents the data of the remaining amount of the patient beds;
h2: according to the calculation formula in H1, the data of the remaining amount of equipment, E3, E4 and the image factor v2 of the sick bed damage when the equipment warning signal occurs are taken in, and the number G2 of the equipment which is required to be increased urgently is calculated.
The invention has the beneficial effects that:
(1) the acquisition module acquires the logistics information and the attendance information of the hospital and respectively transmits the logistics information and the attendance information to the storage module and the analysis module; the analysis module analyzes and calculates the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency according to the logistics information and the treatment information, calculates the abrasion degree of the equipment and the sickbed according to the abrasion degree, and transmits the abrasion degree calculation results of the equipment and the sickbed to the pre-purchase calculation module; the pre-purchase calculation module calculates the estimated durable time of each sickbed and equipment according to the abrasion degree calculation result of the equipment and the sickbed, the using time data of each sickbed and the using time data of each equipment, calculates the quantity data of the needed sickbed and equipment according to the durable time safety judgment result of the sickbed and the equipment and the residual quantity data of the equipment in the database, analyzes the acquired logistics information and the doctor information through the analysis module, thereby calculating the doctor seeing rate, the using frequency of the sickbed, the disassembling frequency of the sickbed and the using frequency of the equipment, calculates the abrasion degree of the equipment and the sickbed according to the equipment, calculates the data of the needed equipment and the sickbed in the pre-purchase calculation module according to the abrasion degree, makes the data analysis diversified and performs classification analysis on the data, the analysis time is saved, the accuracy of data analysis is improved, and the persuasion of data is improved.
(2) The storage module carries out classified storage according to the logistics information and the treatment information acquired by the acquisition module, the equipment and sickbed abrasion degree calculation results analyzed by the analysis module and the pre-purchase calculation module, the required sickbed and equipment quantity data, the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency, and sends a storage success reminding signal to the intelligent equipment after the storage is finished; after receiving the storage success reminding signal, the intelligent device reminds a user to perform storage checking; through storage module's setting, with logistics information, see the doctor information, the degree of wear of equipment and sick bed, the quantity data of required sick bed and equipment, the rate of seeing the doctor, sick bed frequency of use, sick bed dismantlement frequency and equipment frequency of use classify, and with its respectively store value corresponding see the doctor data unit, sick bed data unit, equipment data unit and demand data unit, the staff of being convenient for seeks data sooner, save the seek time, automatically, carry out appeal calculation to the equipment of hospital, ensure the sufficiency of hospital equipment, save artificial calculation time, avoid appearing the phenomenon that the equipment is not enough, and the work efficiency is improved.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a system block diagram of the present invention.
Detailed Description
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.
Referring to fig. 1, the present invention is a distributed data storage method for hospital logistics management, which is characterized in that the distributed data storage method for hospital logistics management specifically includes the following steps:
the method comprises the following steps: the acquisition module acquires the logistics information and the attendance information of the hospital and respectively transmits the logistics information and the attendance information to the storage module and the analysis module;
step two: the analysis module analyzes and calculates the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency according to the logistics information and the treatment information, calculates the abrasion degree of the equipment and the sickbed according to the abrasion degree, and transmits the abrasion degree calculation results of the equipment and the sickbed to the pre-purchase calculation module;
step three: the pre-purchase calculation module calculates the estimated durable time of each sickbed and equipment according to the abrasion degree calculation results of the equipment and the sickbed, the using time data of each sickbed and the using time data of each equipment, carries out durable time safety judgment on the sickbed and the equipment according to the estimated durable time, calculates the quantity data of the needed sickbed and equipment according to the durable time safety judgment results of the sickbed and the equipment and the residual quantity data of the sickbed and the equipment in the database, and transmits the quantity data to the storage module;
step four: the storage module carries out classified storage according to the logistics information and the treatment information acquired by the acquisition module, the equipment and sickbed abrasion degree calculation results analyzed by the analysis module and the pre-purchase calculation module, the required sickbed and equipment quantity data, the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency, and sends a storage success reminding signal to the intelligent equipment after the storage is finished;
step five: after receiving the storage success reminding signal, the intelligent device reminds a user to perform storage checking;
a distributed data storage system for hospital logistics management comprises an acquisition module, an analysis module, a database, a pre-purchase calculation module, a storage module and intelligent equipment;
the system comprises a collection module, a storage module and an analysis module, wherein the collection module is used for collecting the logistics information and the treatment information of a hospital, the treatment information comprises treatment time data, treatment number data and hospitalization number data, and the logistics information comprises sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data which are respectively transmitted to the storage module and the analysis module;
the analysis module is used for carrying out analysis operation on the visit time data, the number of patients, the number of hospitalized patients, the number of times of sickbed use data, the number of times of sickbed disassembly data, the number of times of equipment use data, the highest temperature data of equipment and the weight data of patients, and the specific operation process of the analysis operation is as follows:
k1: acquiring visit time data, visit number data, hospitalization number data, sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data, sequentially marking the data as JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi, wherein i is 1, 2, 3....... n1, and the JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi correspond one to one;
k2: acquiring the number data of the visitors in a period of time, marking the number data of the visitors at JR1 and JR2, marking the corresponding time data of the visitors as JS1 and JS2, and bringing the data of the visitors together into a calculation formula:
wherein, VThen is turned onExpressed as frequency of visit, PJSJS2-JS1, which indicates the number of treatment times in a certain periodData of the number of patients in the visit, PJRJR2-JR1, expressed as total time within a certain visit time data;
k3: acquiring the number data of the hospitalized people, and bringing the number data of the hospitalized people and the corresponding number data of the visiting people into a calculation formula: the sickbed use frequency data and the corresponding sickbed use time data are brought into a calculation formula together: vBedBCi/BSi, where VBedThe frequency of use of the patient bed is represented, and the patient bed disassembly time data are brought into a calculation formula together: vDisassemblingCXi/CSi, wherein VDisassemblingAnd (3) expressing the sickbed detachment frequency, and bringing the data of the use times of the equipment and the data of the use time of the equipment into a calculation formula together: vIs provided withSCi/SSi, wherein VIs provided withExpressed as the frequency of use of the device;
k4: acquiring the daily highest temperature data of the equipment in a period of time, setting a temperature preset value M, and bringing the temperature preset value M and the highest temperature data of the equipment into a calculation formula: pIs provided with＝VIs provided with*[(SWi-M)*u1+M*u2]Wherein P isIs provided withAnd (3) expressed as the wear degree of the equipment, u1 expressed as the wear coefficient exceeding the preset temperature, u2 expressed as the wear coefficient within the preset temperature range, setting a preset value of the weight of the patient, acquiring the sickbed disassembly frequency, the sickbed use frequency and the weight data of the patient in the K3, and bringing the data and the preset value of the weight of the patient into a calculation formula: pBed＝VDisassembling*u3+VBedU4+ (BTi-m) u5+ m u6, wherein PBedThe wear degree of the sickbed is represented, u3 is a wear coefficient of the sickbed caused by the frequency of sickbed disassembly, u4 is a wear coefficient of the sickbed caused by the frequency of sickbed use, u5 is a wear coefficient of the sickbed caused by damage when a weight preset value is exceeded, u6 is a wear coefficient of the sickbed caused by damage within a weight preset value range, m is a patient weight preset value, and a period of time is defined as the first day of the previous month to the last day of the previous month;
k5: transmitting the abrasion degree of the sickbed and the abrasion degree of the equipment to a pre-purchase calculation module;
the database stores sickbed surplus data and equipment surplus data, the pre-purchase calculation module is used for performing pre-purchase calculation operation on the abrasion degree of the sickbed and the abrasion degree of the equipment, and the specific operation process of the pre-purchase calculation operation is as follows:
c1: acquiring the service time data BSi of each sickbed and the wear degree P of each sickbedBedAnd brings them together into the calculation:
wherein, VWear and tearExpressed as the wear rate of the bed in use, a maximum value of the bed wear is set and is brought into the calculation formula together with the bed wear rate:
wherein, TPreparation ofThe data is expressed as the predicted available time of the sickbed, and F1 is expressed as a preset value of the maximum value of the abrasion degree of the sickbed;
c2: acquiring the service time data SSi of each device and the wear degree P of the deviceIs provided withAnd brings them together into the calculation: vSet of damage＝PIs provided with/SSi, wherein VSet of damageExpressed as the wear rate of the equipment in use, a maximum value of the wear level of the equipment is set and is entered into the calculation equation together with the wear rate of the equipment:
wherein S isPreparation ofExpressing the predicted available time data of the equipment, and F2 expressing the preset value of the maximum value of the wear degree of the equipment;
c3: obtaining a predicted time of use T for each bed and each devicePreparation ofAnd SPreparation ofSetting preset safe use time values A1 and A2 of the sickbed and the equipment respectively, and comparing the preset safe use time values with the expected use time of each sickbed and each equipment to obtain a difference value CT between the expected use time values and the preset safe use time values of the sickbed and the equipmentPreparation ofAnd CSPreparation of；
C4: setting the difference between a patient bed and the deviceSetting the values B1 and B2, and comparing the difference CT between the expected use time and the preset safe use time of the sickbed and equipment in the C3Preparation ofAnd CSPreparation ofAnd (3) carrying out comparison, wherein the specific comparison result is as follows: aiming at a sickbed: when CTPreparation ofWhen the time is less than or equal to B1, the patient bed is judged to have short service life and needs to be replaced in time, a patient bed replacement signal is generated, and when CT is carried outPreparation ofWhen the length of the life time of the sickbed is greater than B1, the sickbed is judged to have long service life, the sickbed can be continuously used, a sickbed warning signal is generated, and the life time of the sickbed is determined according to the following conditions: when CS is usedPreparation ofWhen the time is B2 or less, the device is judged to have a short service life and to be replaced in time, a device replacement signal is generated, and when CS is usedPreparation ofIf the length is more than B2, judging that the duration of the sickbed is long, and generating an equipment warning signal by continuously using the sickbed;
c5: the times of occurrence of the sickbed replacement signal, the sickbed warning signal, the equipment replacement signal and the equipment warning signal are extracted and marked as E1, E2, E3 and E4, and are compared with sickbed residual data and equipment residual data in a database, and the method specifically comprises the following steps:
h1: using the calculation: g1 ═ E1+ E2 × v1-L1, and the amount of the patient beds which need to be increased is calculated, wherein G1 represents the number of the patient beds which need to be increased, v1 represents an image factor of the damage of the patient beds when the patient bed warning signal occurs, and L1 represents the data of the remaining amount of the patient beds;
h2: according to the calculation formula in H1, carrying in the data of the residual amount of the equipment, E3, E4 and the image factor v2 of the sickbed damage when the equipment warning signal occurs, and calculating the quantity G2 of the equipment which is required to be increased urgently;
h3: the number of sickbeds which need to be increased urgently and the number of equipment which need to be increased urgently in the H1 and H2 are transmitted to a storage module together;
the storage module comprises a hospital data unit, a hospital bed data unit, an equipment data unit and a demand data unit, and the storage module is used for performing distributed storage on the emergency demand of increasing the number of sickbeds, the emergency demand of increasing the number of equipment, the hospital time data, the hospital number data, the hospital bed use time data, the hospital bed disassembly time data, the equipment use time data, the equipment maximum temperature data and the patient weight data, the hospital frequency, the hospital bed use frequency, the hospital bed disassembly frequency, the equipment use frequency, the abrasion degree of the hospital bed and the abrasion degree of the equipment, and specifically comprises the following steps: the hospital information storage system comprises a hospital information storage unit, a hospital information storage unit and a hospital information.
And after receiving the storage success reminding signal, the intelligent equipment reminds the user to carry out storage checking.
When the hospital information acquisition system works, the acquisition module acquires the logistics information and the attendance information of a hospital and respectively transmits the logistics information and the attendance information to the storage module and the analysis module; the analysis module analyzes and calculates the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency according to the logistics information and the treatment information, calculates the abrasion degree of the equipment and the sickbed according to the abrasion degree, and transmits the abrasion degree calculation results of the equipment and the sickbed to the pre-purchase calculation module; the pre-purchase calculation module calculates the estimated durable time of each sickbed and equipment according to the abrasion degree calculation results of the equipment and the sickbed, the using time data of each sickbed and the using time data of each equipment, carries out durable time safety judgment on the sickbed and the equipment according to the estimated durable time, calculates the quantity data of the needed sickbed and equipment according to the durable time safety judgment results of the sickbed and the equipment and the residual quantity data of the sickbed and the equipment in the database, and transmits the quantity data to the storage module; the storage module carries out classified storage according to the logistics information and the treatment information acquired by the acquisition module, the equipment and sickbed abrasion degree calculation results analyzed by the analysis module and the pre-purchase calculation module, the required sickbed and equipment quantity data, the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency, and sends a storage success reminding signal to the intelligent equipment after the storage is finished; and after receiving the storage success reminding signal, the intelligent equipment reminds the user to carry out storage checking.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (2)
1. A distributed data storage method for hospital logistics management is characterized by specifically comprising the following steps of:
the method comprises the following steps: the acquisition module acquires the logistics information and the attendance information of the hospital and respectively transmits the logistics information and the attendance information to the storage module and the analysis module;
step two: the analysis module analyzes and calculates the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency according to the logistics information and the treatment information, calculates the abrasion degree of the equipment and the sickbed according to the abrasion degree, and transmits the abrasion degree calculation results of the equipment and the sickbed to the pre-purchase calculation module;
step three: the pre-purchase calculation module calculates the estimated durable time of each sickbed and equipment according to the abrasion degree calculation results of the equipment and the sickbed, the using time data of each sickbed and the using time data of each equipment, carries out durable time safety judgment on the sickbed and the equipment according to the estimated durable time, calculates the quantity data of the needed sickbed and equipment according to the durable time safety judgment results of the sickbed and the equipment and the residual quantity data of the sickbed and the equipment in the database, and transmits the quantity data to the storage module;
step four: the storage module carries out classified storage according to the logistics information and the treatment information acquired by the acquisition module, the equipment and sickbed abrasion degree calculation results analyzed by the analysis module and the pre-purchase calculation module, the required sickbed and equipment quantity data, the treatment rate, the sickbed use frequency, the sickbed disassembly frequency and the equipment use frequency, and sends a storage success reminding signal to the intelligent equipment after the storage is finished;
step five: after receiving the storage success reminding signal, the intelligent device reminds a user to perform storage checking;
the clinic information comprises clinic time data, clinic number data and hospitalization number data, and the logistics information comprises sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data;
the calculation in the analysis module specifically comprises the following steps:
k1: acquiring visit time data, visit number data, hospitalization number data, sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data, sequentially marking the data as JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi, wherein i is 1, 2, 3....... n1, and the JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi correspond one to one;
k2: acquiring the number data of the visitors in a period of time, marking the number data of the visitors at JR1 and JR2, marking the corresponding time data of the visitors as JS1 and JS2, and bringing the data of the visitors together into a calculation formula:
wherein, VThen is turned onExpressed as frequency of visit, PJSJS2-JS1, which represents the number of visits within a certain visit time data, PJRJR2-JR1, expressed as total time within a certain visit time data;
k3: acquiring the number data of the hospitalized people, and bringing the number data of the hospitalized people and the corresponding number data of the visiting people into a calculation formula: will be provided withThe sickbed use time data and the corresponding sickbed use time data are brought into a calculation formula together: vBedBCi/BSi, where VBedThe frequency of use of the patient bed is represented, and the patient bed disassembly time data are brought into a calculation formula together: vDisassemblingCXi/CSi, wherein VDisassemblingAnd (3) expressing the sickbed detachment frequency, and bringing the data of the use times of the equipment and the data of the use time of the equipment into a calculation formula together: vIs provided withSCi/SSi, wherein VIs provided withExpressed as the frequency of use of the device;
k4: acquiring the daily highest temperature data of the equipment in a period of time, setting a temperature preset value M, and bringing the temperature preset value M and the highest temperature data of the equipment into a calculation formula: pIs provided with＝VIs provided with*[(SWi-M)*u1+M*u2]Wherein P isIs provided withAnd (3) expressed as the wear degree of the equipment, u1 expressed as the wear coefficient exceeding the preset temperature, u2 expressed as the wear coefficient within the preset temperature range, setting a preset value of the weight of the patient, acquiring the sickbed disassembly frequency, the sickbed use frequency and the weight data of the patient in the K3, and bringing the data and the preset value of the weight of the patient into a calculation formula: pBed＝VDisassembling*u3+VBedU4+ (BTi-m) u5+ m u6, wherein PBedThe wear degree of the sickbed is represented, u3 is a wear coefficient of the sickbed caused by the frequency of sickbed disassembly, u4 is a wear coefficient of the sickbed caused by the frequency of sickbed use, u5 is a wear coefficient of the sickbed caused by damage when a weight preset value is exceeded, u6 is a wear coefficient of the sickbed caused by damage within a weight preset value range, m is a patient weight preset value, and a period of time is defined as the first day of the previous month to the last day of the previous month;
k5: transmitting the abrasion degree of the sickbed and the abrasion degree of the equipment to a pre-purchase calculation module;
the specific calculation process in the pre-purchase calculation module is as follows:
c1: acquiring the service time data BSi of each sickbed and the wear degree P of each sickbedBedAnd brings them together into the calculation:
wherein, VWear and tearExpressed as the wear rate of the bed in use, a maximum value of the bed wear is set and is brought into the calculation formula together with the bed wear rate:
wherein, TPreparation ofThe data is expressed as the predicted available time of the sickbed, and F1 is expressed as a preset value of the maximum value of the abrasion degree of the sickbed;
c2: acquiring the service time data SSi of each device and the wear degree P of the deviceIs provided withAnd brings them together into the calculation: vSet of damage＝PIs provided with/SSi, wherein VSet of damageExpressed as the wear rate of the equipment in use, a maximum value of the wear level of the equipment is set and is entered into the calculation equation together with the wear rate of the equipment:
wherein S isPreparation ofExpressing the predicted available time data of the equipment, and F2 expressing the preset value of the maximum value of the wear degree of the equipment;
c3: obtaining a predicted time of use T for each bed and each devicePreparation ofAnd SPreparation ofSetting preset safe use time values A1 and A2 of the sickbed and the equipment respectively, and comparing the preset safe use time values with the expected use time of each sickbed and each equipment to obtain a difference value CT between the expected use time values and the preset safe use time values of the sickbed and the equipmentPreparation ofAnd CSPreparation of；
C4: setting a difference preset value B1 and B2 of the sickbed and the equipment respectively, and comparing the difference CT with the preset value of the predicted use time and the safe use time of the sickbed and the equipment in the C3Preparation ofAnd CSPreparation ofAnd (3) carrying out comparison, wherein the specific comparison result is as follows: aiming at a sickbed: when CTPreparation ofWhen the time is less than or equal to B1, the patient bed is judged to have short service life and needs to be replaced in time, a patient bed replacement signal is generated, and when CT is carried outPreparation ofIf the height is more than B1, the tolerance of the sickbed is judgedThe time is big, continues to use this sick bed, generates sick bed warning signal, to equipment: when CS is usedPreparation ofWhen the time is B2 or less, the device is judged to have a short service life and to be replaced in time, a device replacement signal is generated, and when CS is usedPreparation ofIf the length is more than B2, judging that the duration of the sickbed is long, continuing to use the sickbed and generating an equipment warning signal;
c5: the times of occurrence of the sickbed replacement signal, the sickbed warning signal, the equipment replacement signal and the equipment warning signal are extracted and marked as E1, E2, E3 and E4, and are compared with sickbed residual data and equipment residual data in a database, and the method specifically comprises the following steps:
h1: using the calculation: g1 ═ E1+ E2 × v1-L1, and the amount of the patient beds which need to be increased is calculated, wherein G1 represents the number of the patient beds which need to be increased, v1 represents an image factor of the damage of the patient beds when the patient bed warning signal occurs, and L1 represents the data of the remaining amount of the patient beds;
h2: according to the calculation formula in H1, carrying in the data of the residual amount of the equipment, E3, E4 and the image factor v2 of the sickbed damage when the equipment warning signal occurs, and calculating the quantity G2 of the equipment which is required to be increased urgently;
h3: the number of the sickbeds which need to be increased urgently and the number of the equipment which needs to be increased urgently in the H1 and H2 are transmitted to the storage module together.
2. A distributed data storage system for hospital logistics management is characterized by comprising an acquisition module, an analysis module, a database, a pre-purchase calculation module, a storage module and intelligent equipment;
the system comprises a collection module, a storage module and an analysis module, wherein the collection module is used for collecting the logistics information and the treatment information of a hospital, the treatment information comprises treatment time data, treatment number data and hospitalization number data, and the logistics information comprises sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data which are respectively transmitted to the storage module and the analysis module;
the analysis module is used for carrying out analysis operation on the visit time data, the number of patients, the number of hospitalized patients, the number of times of sickbed use data, the number of times of sickbed disassembly data, the number of times of equipment use data, the highest temperature data of equipment and the weight data of patients, and the specific operation process of the analysis operation is as follows:
k1: acquiring visit time data, visit number data, hospitalization number data, sickbed use time data, sickbed disassembly time data, equipment use time data, equipment highest temperature data and patient weight data, sequentially marking the data as JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi, wherein i is 1, 2, 3....... n1, and the JSi, JRi, ZRi, BCi, BSi, CXi, CSi, SCi, SSi, SWi and BTi correspond one to one;
k2: acquiring the number data of the visitors in a period of time, marking the number data of the visitors at JR1 and JR2, marking the corresponding time data of the visitors as JS1 and JS2, and bringing the data of the visitors together into a calculation formula:
wherein, VThen is turned onExpressed as frequency of visit, PJSJS2-JS1, which represents the number of visits within a certain visit time data, PJRJR2-JR1, expressed as total time within a certain visit time data;
k3: acquiring the number data of the hospitalized people, and bringing the number data of the hospitalized people and the corresponding number data of the visiting people into a calculation formula: the sickbed use frequency data and the corresponding sickbed use time data are brought into a calculation formula together: vBedBCi/BSi, where VBedThe frequency of use of the patient bed is represented, and the patient bed disassembly time data are brought into a calculation formula together: vDisassemblingCXi/CSi, wherein VDisassemblingAnd (3) expressing the sickbed detachment frequency, and bringing the data of the use times of the equipment and the data of the use time of the equipment into a calculation formula together: vIs provided withSCi/SSi, wherein VIs provided withExpressed as the frequency of use of the device;
k4: acquiring the daily highest temperature data of the equipment in a period of time, setting a temperature preset value M, and bringing the temperature preset value M and the highest temperature data of the equipment into a calculation formula: pIs provided with＝VIs provided with*[(SWi-M)*u1+M*u2]Wherein P isIs provided withAnd (3) expressed as the wear degree of the equipment, u1 expressed as the wear coefficient exceeding the preset temperature, u2 expressed as the wear coefficient within the preset temperature range, setting a preset value of the weight of the patient, acquiring the sickbed disassembly frequency, the sickbed use frequency and the weight data of the patient in the K3, and bringing the data and the preset value of the weight of the patient into a calculation formula: pBed＝VDisassembling*u3+VBedU4+ (BTi-m) u5+ m u6, wherein PBedThe wear degree of the sickbed is represented, u3 is a wear coefficient of the sickbed caused by the frequency of sickbed disassembly, u4 is a wear coefficient of the sickbed caused by the frequency of sickbed use, u5 is a wear coefficient of the sickbed caused by damage when a weight preset value is exceeded, u6 is a wear coefficient of the sickbed caused by damage within a weight preset value range, m is a patient weight preset value, and a period of time is defined as the first day of the previous month to the last day of the previous month;
k5: transmitting the abrasion degree of the sickbed and the abrasion degree of the equipment to a pre-purchase calculation module;
the database stores sickbed surplus data and equipment surplus data, the pre-purchase calculation module is used for performing pre-purchase calculation operation on the abrasion degree of the sickbed and the abrasion degree of the equipment, and the specific operation process of the pre-purchase calculation operation is as follows:
c1: acquiring the service time data BSi of each sickbed and the wear degree P of each sickbedBedAnd brings them together into the calculation:
wherein, VWear and tearExpressed as the wear rate of the bed in use, a maximum value of the bed wear is set and is brought into the calculation formula together with the bed wear rate:
wherein, TPreparation ofThe data is expressed as the predicted available time of the sickbed, and F1 is expressed as a preset value of the maximum value of the abrasion degree of the sickbed;
c2: acquiring the service time data SSi of each device and the wear degree P of the deviceIs provided withAnd brings them together into the calculation: vSet of damage＝PIs provided with/SSi, wherein VSet of damageExpressed as the wear rate of the equipment in use, a maximum value of the wear level of the equipment is set and is entered into the calculation equation together with the wear rate of the equipment:
wherein S isPreparation ofExpressing the predicted available time data of the equipment, and F2 expressing the preset value of the maximum value of the wear degree of the equipment;
c3: obtaining a predicted time of use T for each bed and each devicePreparation ofAnd SPreparation ofSetting preset safe use time values A1 and A2 of the sickbed and the equipment respectively, and comparing the preset safe use time values with the expected use time of each sickbed and each equipment to obtain a difference value CT between the expected use time values and the preset safe use time values of the sickbed and the equipmentPreparation ofAnd CSPreparation of；
C4: setting a difference preset value B1 and B2 of the sickbed and the equipment respectively, and comparing the difference CT with the preset value of the predicted use time and the safe use time of the sickbed and the equipment in the C3Preparation ofAnd CSPreparation ofAnd (3) carrying out comparison, wherein the specific comparison result is as follows: aiming at a sickbed: when CTPreparation ofWhen the time is less than or equal to B1, the patient bed is judged to have short service life and needs to be replaced in time, a patient bed replacement signal is generated, and when CT is carried outPreparation ofWhen the length of the life time of the sickbed is greater than B1, the sickbed is judged to have long service life, the sickbed is continuously used, a sickbed warning signal is generated, and the length of the sickbed warning signal is as follows: when CS is usedPreparation ofWhen the time is B2 or less, the device is judged to have a short service life and to be replaced in time, a device replacement signal is generated, and when CS is usedPreparation ofIf the length is more than B2, the duration of the sickbed is judged to be long, the sickbed is continuously used, and an equipment alarm is generatedShowing a signal;
c5: the times of occurrence of the sickbed replacement signal, the sickbed warning signal, the equipment replacement signal and the equipment warning signal are extracted and marked as E1, E2, E3 and E4, and are compared with sickbed residual data and equipment residual data in a database, and the method specifically comprises the following steps:
h1: using the calculation: g1 ═ E1+ E2 × v1-L1, and the amount of the patient beds which need to be increased is calculated, wherein G1 represents the number of the patient beds which need to be increased, v1 represents an image factor of the damage of the patient beds when the patient bed warning signal occurs, and L1 represents the data of the remaining amount of the patient beds;
h2: according to the calculation formula in H1, carrying in the data of the residual amount of the equipment, E3, E4 and the image factor v2 of the sickbed damage when the equipment warning signal occurs, and calculating the quantity G2 of the equipment which is required to be increased urgently;
h3: the number of sickbeds which need to be increased urgently and the number of equipment which need to be increased urgently in the H1 and H2 are transmitted to a storage module together;
the storage module comprises a hospital data unit, a hospital bed data unit, an equipment data unit and a demand data unit, and the storage module is used for performing distributed storage on the emergency demand of increasing the number of sickbeds, the emergency demand of increasing the number of equipment, the hospital time data, the hospital number data, the hospital bed use time data, the hospital bed disassembly time data, the equipment use time data, the equipment maximum temperature data and the patient weight data, the hospital frequency, the hospital bed use frequency, the hospital bed disassembly frequency, the equipment use frequency, the abrasion degree of the hospital bed and the abrasion degree of the equipment, and specifically comprises the following steps: storing the time data of the patient, the number data of the patient, the weight data of the patient, the number data of the hospitalized patient and the frequency of the patient to a data unit of the patient, storing the data of the using times of the sickbed, the using time data of the sickbed, the data of the detaching times of the sickbed, the data of the detaching time of the sickbed, the using frequency of the sickbed and the detaching frequency of the sickbed to a data unit of the sickbed, storing the data of the using times of the equipment, the data of the using time of the equipment, the data of the highest temperature of the equipment and the using frequency of the equipment to a data unit of the equipment, storing the quantity of the sickbed which is urgently needed to be increased;
and after receiving the storage success reminding signal, the intelligent equipment reminds the user to carry out storage checking.
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