CN117253577B - Multidimensional health data integrated processing system - Google Patents
Multidimensional health data integrated processing system Download PDFInfo
- Publication number
- CN117253577B CN117253577B CN202311534606.9A CN202311534606A CN117253577B CN 117253577 B CN117253577 B CN 117253577B CN 202311534606 A CN202311534606 A CN 202311534606A CN 117253577 B CN117253577 B CN 117253577B
- Authority
- CN
- China
- Prior art keywords
- region
- vaccine
- personnel
- information
- estimated
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 230000036541 health Effects 0.000 title claims abstract description 14
- 229960005486 vaccine Drugs 0.000 claims abstract description 128
- 238000002255 vaccination Methods 0.000 claims abstract description 85
- 206010067484 Adverse reaction Diseases 0.000 claims abstract description 50
- 230000006838 adverse reaction Effects 0.000 claims abstract description 50
- 238000000034 method Methods 0.000 claims abstract description 46
- 238000011156 evaluation Methods 0.000 claims description 55
- 238000004458 analytical method Methods 0.000 claims description 41
- 238000006243 chemical reaction Methods 0.000 claims description 29
- 201000010099 disease Diseases 0.000 claims description 17
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 claims description 17
- 238000004364 calculation method Methods 0.000 claims description 15
- 230000005540 biological transmission Effects 0.000 claims description 6
- 238000006467 substitution reaction Methods 0.000 claims description 3
- 238000002360 preparation method Methods 0.000 abstract description 5
- 238000009826 distribution Methods 0.000 abstract description 4
- 238000012502 risk assessment Methods 0.000 abstract description 4
- 230000002349 favourable effect Effects 0.000 abstract 1
- 230000003449 preventive effect Effects 0.000 description 7
- 230000007774 longterm Effects 0.000 description 6
- 238000011081 inoculation Methods 0.000 description 3
- 238000007405 data analysis Methods 0.000 description 2
- 238000002156 mixing Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 208000023275 Autoimmune disease Diseases 0.000 description 1
- 206010020751 Hypersensitivity Diseases 0.000 description 1
- 206010061598 Immunodeficiency Diseases 0.000 description 1
- 208000029462 Immunodeficiency disease Diseases 0.000 description 1
- 206010037660 Pyrexia Diseases 0.000 description 1
- 230000002159 abnormal effect Effects 0.000 description 1
- 208000030961 allergic reaction Diseases 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 150000002402 hexoses Chemical class 0.000 description 1
- 230000036737 immune function Effects 0.000 description 1
- 230000003053 immunization Effects 0.000 description 1
- 238000002649 immunization Methods 0.000 description 1
- 230000007813 immunodeficiency Effects 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000005180 public health Effects 0.000 description 1
- 230000008961 swelling Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- 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
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- 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
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/80—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for detecting, monitoring or modelling epidemics or pandemics, e.g. flu
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Health & Medical Sciences (AREA)
- Engineering & Computer Science (AREA)
- Public Health (AREA)
- Medical Informatics (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Business, Economics & Management (AREA)
- General Business, Economics & Management (AREA)
- Biomedical Technology (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Pathology (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a multidimensional health data integrated processing system, which relates to the technical field of data integrated processing. According to the information, the vaccine demand of different areas can be estimated more accurately, and reasonable vaccine distribution can be performed. The method is favorable for ensuring reasonable utilization of vaccine resources, avoiding the situation of excessive or insufficient vaccine in certain areas, facilitating vaccine supply and vaccination preparation work to be done in advance, carrying out risk assessment and taking corresponding precautions by judging that a certain type of vaccine in the area is easy to generate adverse reaction, reducing the occurrence of adverse reaction, guaranteeing the safety of vaccinated people, and increasing the confidence and the vaccination willingness of the public for vaccination.
Description
Technical Field
The invention relates to the technical field of data integrated processing, in particular to a multidimensional health and health data integrated processing system.
Background
Immunization is a reaction of the body for identifying oneself and non-hexose and heterohexose, when abnormal immune function occurs, the adverse reactions such as allergic reaction, immunodeficiency, autoimmune disease and the like can be shown, the individual can be protected by preventive inoculation, the disability and death caused by the disease can be prevented, the disease burden can also be reduced by protecting the group, and the disease is eliminated until the disease is eradicated, so that the quantity of vaccinations in each region needs to be estimated in order to help ensure the balance of vaccine supply, the reasonable distribution of resources and the scientificity of decisions;
the prior art only relies on real-time data analysis and processing, which may lead to lack of long-term planning, failure to perform trend analysis and prediction, only focusing on real-time data, and failure to timely discover and cope with problems possibly occurring in the future, and obviously, the analysis mode has at least the following problems:
1. the current technology cannot predict the number of vaccinations in each region, which may lead to unbalanced vaccine supply. Some areas may have vaccine shortages, while other areas may have excess vaccine. This may result in some areas where people cannot vaccinate in time, increasing the risk of infection by disease, relying solely on real-time data analysis and processing, possibly resulting in a lack of long-term planning. Long-term planning is critical to the success of vaccination efforts, such as determining vaccination strategies, planning vaccine supply and constructing vaccination points, etc. If only real-time data is of interest, long-term demands and trends may not be fully considered, thereby affecting the sustainability and effectiveness of vaccination efforts;
2. meanwhile, adverse reactions are an important issue in vaccination procedures, and are critical to public health and safety. If it is impossible to accurately judge which type of vaccine is likely to have adverse reactions, effective risk assessment cannot be performed. This may lead to a threat to the safety of the vaccination effort, increasing public concern and distrust about vaccination, and reduced public trust in vaccination. This may lead to a reduced enthusiasm for vaccination by the public, thereby affecting the coverage and effectiveness of the vaccination effort.
Disclosure of Invention
In view of the above-mentioned technical shortcomings, the present invention aims to provide a multidimensional health data integrated processing system.
In order to solve the technical problems, the invention adopts the following technical scheme: the invention provides a multidimensional health data integrated processing system, which comprises: and a data acquisition module: the method comprises the steps of acquiring personnel information, illness state information and medical resource information corresponding to each region, and further acquiring personnel information, illness state information and medical resource information in each region, wherein the personnel information comprises population number, population density and population growth rate, the illness state information comprises case number and transmission speed, and the medical resource information comprises hospital number, doctor number and medical facility number;
analysis module of personnel, illness state and medical quality information: the system is used for analyzing the personnel information corresponding to each region according to the personnel information, the illness state information and the medical resource information corresponding to each region, so as to obtain personnel evaluation coefficients corresponding to the personnel information of each region, so as to analyze the illness state information corresponding to each region, so as to obtain illness state evaluation coefficients corresponding to the illness state information of each region, so as to analyze the medical resource information corresponding to each region, and further obtain medical resource evaluation coefficients corresponding to the medical resource information of each region;
vaccination analysis module: the method comprises the steps of carrying out pre-estimation analysis on vaccination conditions corresponding to each region according to personnel assessment coefficients, illness state assessment coefficients and medical resource assessment coefficients corresponding to each region, and further obtaining pre-estimation assessment coefficients corresponding to vaccination conditions of each region;
an estimated module of vaccination: the method comprises the steps of obtaining the estimated quantity of vaccinations in each region according to the estimated evaluation coefficients corresponding to vaccinations in each region;
inventory analysis and deployment module for vaccine: the method comprises the steps of calculating a difference value according to the estimated quantity of vaccinations in each region and the actual quantity of vaccine stock in the corresponding region, so as to obtain a difference value between the estimated quantity of vaccinations in each region and the actual quantity of vaccine stock in the corresponding region, and allocating the actual quantity of vaccine stock in each region;
the acquisition module of the adverse reaction quantity: the method is used for collecting the number of the adverse reaction personnel corresponding to each type of vaccine, and further obtaining the number of the adverse reaction personnel corresponding to each type of vaccine;
analysis module of vaccine adverse reaction: the method is used for analyzing the number of the adverse reaction personnel corresponding to each type of vaccine according to the number of the adverse reaction personnel corresponding to each type of vaccine to obtain the occurrence rate of the number of the adverse reaction personnel corresponding to each type of vaccine, and further judging whether the adverse reaction of each type of vaccine is easy to occur;
early warning terminal: the method is used for carrying out early warning prompt when a certain type of vaccine is easy to cause adverse reaction.
Preferably, the analyzing the personnel information corresponding to each region includes the following specific analysis process:
the population number, population density and population growth rate in each region are respectively recorded as、/>And->Wherein->Indicating the corresponding numbers of the areas, +.>Substituting the calculation formula +.>In the method, personnel evaluation coefficients corresponding to personnel information of each region are obtained>Wherein->、/>、/>Respectively expressed as the preset regional corresponding standard population quantity, standard population density, standard population growth rate, +.>、/>、/>Respectively expressed as weight factors corresponding to regional population number, population density and population growth rate.
Preferably, the analyzing the disease information corresponding to each region specifically includes the following steps:
the number of cases and the transmission speed in each region are respectively recorded asAnd->Wherein->The corresponding numbers of the areas are indicated,substituting the calculation formula +.>Obtaining the disease condition evaluation coefficient corresponding to the disease condition information of each region>Wherein->、/>Respectively expressed as the number of standard cases and standard propagation speed corresponding to the preset region, < + >>、Respectively expressed as the number of cases in the region and the weight factor corresponding to the propagation speed.
Preferably, the analyzing the medical resource information corresponding to each region specifically includes the following steps:
the number of hospitals, doctors and medical facilities in each region are respectively recorded as、/>And->Wherein->Indicating the corresponding numbers of the areas, +.>Substituting the calculation formula +.>Obtaining medical resource evaluation coefficients corresponding to the medical resource information of each region>Wherein->、/>、/>Respectively expressed as the number of standard hospitals, the number of standard doctors and the number of standard medical facilities corresponding to the preset region,/for the preset region>、/>、/>Respectively expressed as weight factors corresponding to the number of hospitals, doctors and medical facilities in the region.
Preferably, the pre-estimated analysis is performed on the vaccination conditions corresponding to each region, and the specific analysis process is as follows;
personnel evaluation coefficients corresponding to personnel information of each regionDisease evaluation coefficient corresponding to disease information of each region>Medical resource evaluation coefficient corresponding to medical resource information +.>Substitution of the calculation formula +.>Obtaining estimated evaluation coefficients corresponding to vaccination conditions in each region>，/>、/>、/>Respectively set personnel evaluation coefficients, illness evaluation coefficients and weight factors corresponding to medical resource evaluation coefficients.
Preferably, the obtaining the estimated number of vaccinations in each region specifically comprises the following steps:
comparing the estimated evaluation coefficients corresponding to the vaccination conditions of each region with the set estimated evaluation coefficients corresponding to the vaccination conditions of the regions, so as to obtain the estimated quantity of vaccinations corresponding to the estimated evaluation coefficients of the vaccination conditions of each region, and further obtain the estimated quantity of vaccinations of each region.
Preferably, the actual amount of vaccine stock in each region is prepared, and the specific preparation process is as follows:
a1, calculating a difference value between the estimated quantity of vaccinations in each region and the actual quantity of vaccine stocks in the corresponding region, wherein the difference value is obtained by subtracting the actual quantity of vaccine stocks in the corresponding region from the estimated quantity of vaccinations in each region, so as to judge that the actual quantity of vaccine stocks in each region is too high or too low;
a2, when the actual number of vaccine stocks in each determination area is too large or too small, further blending the actual number of vaccine stocks in the determination area to the area with too small actual number of vaccine stocks in the determination area.
Preferably, the number of the adverse reaction personnel corresponding to each type of vaccine is analyzed, and the specific analysis process is as follows:
counting total number of vaccinators corresponding to each type of vaccine, and marking asCounting the number of adverse reaction people corresponding to various types of vaccines, and marking as +.>Wherein->Numbers representing the correspondence of the various types, +.>Substituting the calculation formula +.>The number incidence of adverse reaction personnel corresponding to various types of vaccines is obtained>。
Preferably, the specific judging process is as follows:
comparing the occurrence rate of the number of the untoward reaction personnel corresponding to each type of vaccine with the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine, judging that the type of vaccine is not easy to cause untoward reaction if the occurrence rate of the number of the untoward reaction personnel corresponding to a certain type of vaccine is smaller than or equal to the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine, and judging that the type of vaccine is easy to cause untoward reaction if the occurrence rate of the number of the untoward reaction personnel corresponding to a certain type of vaccine is larger than the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine.
The invention has the beneficial effects that:
1. according to the invention, the epidemic situation and population requirements of different areas can be known by analyzing the personnel information and the illness state information of each area. According to the information, the vaccine demand of different areas can be estimated more accurately, and reasonable vaccine distribution can be performed. The method is helpful for ensuring reasonable utilization of vaccine resources, avoiding the situation of excessive or insufficient vaccine in certain areas, facilitating the preparation work of vaccine supply and inoculation in advance, and avoiding the situation of vaccine shortage or unbalanced supply and demand; predicting future demands may also help in making long-term plans and decisions to ensure sustainability and effectiveness of vaccination efforts;
2. meanwhile, by judging that a certain type of vaccine in the area is easy to cause adverse reaction, risk assessment can be carried out, corresponding preventive measures can be taken, the occurrence of adverse reaction can be reduced, the safety of vaccinated people is guaranteed, after knowing that a certain type of vaccine is easy to cause adverse reaction, corresponding measures can be taken, the preventive effect of vaccination can be ensured, the influence of the adverse reaction on vaccinated people is reduced, and the confidence and the willingness of vaccination of the public to vaccinate can be increased by taking corresponding preventive measures.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the system module connection of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
An embodiment of the present invention is shown in fig. 1, and a multidimensional health data integrated processing system includes: the system comprises a data acquisition module, a personnel, an analysis module of illness state and medical quality information, a vaccination analysis module, a vaccination prediction module, a vaccine inventory analysis and allocation module, an acquisition module of adverse reaction quantity, an analysis module of vaccine adverse reaction and an early warning terminal.
The analysis module of personnel, illness state and medical quality information is respectively connected with the data acquisition module and the analysis module of vaccination, the prediction module of vaccination is respectively connected with the analysis module of vaccination and the inventory analysis and allocation module of vaccination, the acquisition module of adverse reaction quantity is respectively connected with the inventory analysis and allocation module of vaccination and the analysis module of adverse reaction of vaccination, and the analysis module of adverse reaction of vaccination is connected with the early warning terminal.
And a data acquisition module: the method is used for collecting personnel information, illness state information and medical resource information corresponding to each region, further obtaining personnel information, illness state information and medical resource information in each region, wherein the personnel information comprises population number, population density and population growth rate, the illness state information comprises case number and transmission speed, and the medical resource information comprises hospital number, doctor number and medical facility number.
Analysis module of personnel, illness state and medical quality information: the system is used for analyzing the personnel information corresponding to each region according to the personnel information, the illness state information and the medical resource information corresponding to each region, further obtaining personnel evaluation coefficients corresponding to the personnel information of each region, further analyzing the illness state information corresponding to each region, further obtaining illness state evaluation coefficients corresponding to the illness state information of each region, further analyzing the medical resource information corresponding to each region, and further obtaining the medical resource evaluation coefficients corresponding to the medical resource information of each region.
In a specific embodiment, the analyzing the personnel information corresponding to each region specifically includes the following steps:
the population number, population density and population growth rate in each region are respectively recorded as、/>And->Wherein->Indicating the corresponding numbers of the areas, +.>Substituting the calculation formula +.>In the method, personnel evaluation coefficients corresponding to personnel information of each region are obtained>Wherein->、/>、/>Respectively expressed as the preset regional corresponding standard population quantity, standard population density, standard population growth rate, +.>、/>、/>Respectively expressed as weight factors corresponding to regional population number, population density and population growth rate.
The population number, population density and population growth rate of each region are obtained by a census agency.
In another specific embodiment, the analyzing the disease information corresponding to each region specifically includes the following steps:
the number of cases and the transmission speed in each region are respectively recorded asAnd->Wherein->The corresponding numbers of the areas are indicated,substituting the calculation formula +.>Obtaining the disease condition evaluation coefficient corresponding to the disease condition information of each region>Wherein->、/>Respectively expressed as the number of standard cases and standard propagation speed corresponding to the preset region, < + >>、Respectively expressed as the number of cases in the region and the weight factor corresponding to the propagation speed.
The number of cases and the propagation speed in each region were obtained by the health department.
In another specific embodiment, the analyzing the medical resource information corresponding to each region specifically includes the following steps:
the number of hospitals, doctors and medical facilities in each region are respectively recorded as、/>And->Wherein->Indicating the corresponding numbers of the areas, +.>Substituting the calculation formula +.>Obtaining medical resource evaluation coefficients corresponding to the medical resource information of each region>Wherein->、/>、/>Respectively expressed as the number of standard hospitals, the number of standard doctors and the number of standard medical facilities corresponding to the preset region,/for the preset region>、/>、/>Respectively expressed as weight factors corresponding to the number of hospitals, doctors and medical facilities in the region.
The number of hospitals, the number of doctors, and the number of medical facilities in each area were obtained by the health institutions.
Vaccination analysis module: the method is used for carrying out pre-estimated analysis on the vaccination conditions corresponding to each region according to the personnel evaluation coefficient, the illness state evaluation coefficient and the medical resource evaluation coefficient corresponding to each region, so as to obtain the pre-estimated evaluation coefficient corresponding to the vaccination conditions of each region.
In a specific embodiment, the pre-estimated analysis is performed on the vaccination conditions corresponding to each region, and the specific analysis process is as follows;
personnel evaluation coefficients corresponding to personnel information of each regionDisease evaluation coefficient corresponding to disease information of each region>Medical resource evaluation coefficient corresponding to medical resource information +.>Substitution of the calculation formula +.>Obtaining estimated evaluation coefficients corresponding to vaccination conditions in each region>，/>、/>、/>Respectively set personnel evaluation coefficients, illness evaluation coefficients and weight factors corresponding to medical resource evaluation coefficients.
An estimated module of vaccination: the method is used for obtaining the estimated quantity of vaccinations in each region according to the estimated evaluation coefficients corresponding to vaccinations in each region.
The method for obtaining the estimated quantity of vaccinations in each region comprises the following specific obtaining process:
in a specific embodiment, the estimated evaluation coefficients corresponding to the vaccination conditions of each region are compared with the set estimated evaluation coefficients corresponding to the vaccination conditions of the region, so as to obtain the estimated number of vaccinations corresponding to the estimated evaluation coefficients of the vaccination conditions of each region, and further obtain the estimated number of vaccinations of each region.
It should be noted that the vaccine stock refers to the amount of vaccine stored in a medical institution, a health department, or a vaccine manufacturing company, etc., and the purpose of the vaccine stock is to ensure that a sufficient supply amount is provided when vaccination is required to satisfy the public's immune demand.
Inventory analysis and deployment module for vaccine: the method is used for calculating the difference value according to the estimated quantity of vaccinations in each region and the actual quantity of vaccine stock in the corresponding region, so as to obtain the difference value between the estimated quantity of vaccinations in each region and the actual quantity of vaccine stock in the corresponding region, and allocating the actual quantity of vaccine stock in each region.
In a specific embodiment, the actual amount of vaccine stock in each region is prepared by the following specific preparation process:
a1, calculating a difference value between the estimated quantity of vaccinations in each region and the actual quantity of vaccine stocks in the corresponding region, wherein the difference value is obtained by subtracting the actual quantity of vaccine stocks in the corresponding region from the estimated quantity of vaccinations in each region, so as to judge that the actual quantity of vaccine stocks in each region is too high or too low;
a2, when the actual number of vaccine stocks in each determination area is too large or too small, further blending the actual number of vaccine stocks in the determination area to the area with too small actual number of vaccine stocks in the determination area.
It should be noted that vaccines are typically formulated by specialized transportation vehicles.
According to the invention, the epidemic situation and population requirements of different areas can be known by analyzing the personnel information and the illness state information of each area. According to the information, the vaccine demand of different areas can be estimated more accurately, and reasonable vaccine distribution can be performed. The method is helpful for ensuring reasonable utilization of vaccine resources, avoiding the situation of excessive or insufficient vaccine in certain areas, facilitating the preparation work of vaccine supply and inoculation in advance, and avoiding the situation of vaccine shortage or unbalanced supply and demand; predicting future demands may also help in making long-term plans and decisions to ensure sustainability and effectiveness of vaccination efforts.
The acquisition module of the adverse reaction quantity: the method is used for collecting the number of the adverse reaction personnel corresponding to each type of vaccine, and further obtaining the number of the adverse reaction personnel corresponding to each type of vaccine.
Analysis module of vaccine adverse reaction: the method is used for analyzing the number of the untoward reaction personnel corresponding to each type of vaccine according to the number of the untoward reaction personnel corresponding to each type of vaccine, so as to obtain the occurrence rate of the number of the untoward reaction personnel corresponding to each type of vaccine, and further judge whether untoward reaction is easy to occur in each type of vaccine.
It should be noted that adverse reactions including pain, redness, swelling, or induration may occur at the site where the vaccine is injected, and fever may also be caused.
The specific judging process is as follows:
in a specific embodiment, the number of adverse reaction personnel corresponding to each type of vaccine is analyzed, and the specific analysis process is as follows:
counting total number of vaccinators corresponding to each type of vaccine, and marking asCounting the number of adverse reaction people corresponding to various types of vaccines, and marking as +.>Wherein->Numbers representing the correspondence of the various types, +.>Substituting the calculation formula +.>The number incidence of adverse reaction personnel corresponding to various types of vaccines is obtained>。
In another specific embodiment, the specific determination process is as follows:
comparing the occurrence rate of the number of the untoward reaction personnel corresponding to each type of vaccine with the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine, judging that the type of vaccine is not easy to cause untoward reaction if the occurrence rate of the number of the untoward reaction personnel corresponding to a certain type of vaccine is smaller than or equal to the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine, and judging that the type of vaccine is easy to cause untoward reaction if the occurrence rate of the number of the untoward reaction personnel corresponding to a certain type of vaccine is larger than the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine.
Meanwhile, by judging that a certain type of vaccine in the area is easy to cause adverse reaction, risk assessment can be carried out, corresponding preventive measures can be taken, the occurrence of adverse reaction can be reduced, the safety of vaccinated people is guaranteed, after knowing that a certain type of vaccine is easy to cause adverse reaction, corresponding measures can be taken, the preventive effect of vaccination can be ensured, the influence of the adverse reaction on vaccinated people is reduced, and the confidence and the willingness of vaccination of the public to vaccinate can be increased by taking corresponding preventive measures.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (3)
1. A multi-dimensional health data integrated processing system, comprising:
and a data acquisition module: the method comprises the steps of acquiring personnel information, illness state information and medical resource information corresponding to each region, and further acquiring personnel information, illness state information and medical resource information in each region, wherein the personnel information comprises population number, population density and population growth rate, the illness state information comprises case number and transmission speed, and the medical resource information comprises hospital number, doctor number and medical facility number;
analysis module of personnel, illness state and medical quality information: the system is used for analyzing the personnel information corresponding to each region according to the personnel information, the illness state information and the medical resource information corresponding to each region, so as to obtain personnel evaluation coefficients corresponding to the personnel information of each region, so as to analyze the illness state information corresponding to each region, so as to obtain illness state evaluation coefficients corresponding to the illness state information of each region, so as to analyze the medical resource information corresponding to each region, and further obtain medical resource evaluation coefficients corresponding to the medical resource information of each region;
the personnel information corresponding to each region is analyzed, and the specific analysis process is as follows:
the population number, population density and population growth rate in each region are respectively recorded as、/>And->Wherein->Indicating the corresponding numbers of the areas, +.>Substituting the calculation formula +.>In the method, personnel evaluation coefficients corresponding to personnel information of each region are obtained>Wherein->、/>、/>Respectively expressed as the preset regional corresponding standard population quantity, standard population density, standard population growth rate, +.>、/>、/>Respectively expressed as the regional population quantity, population density and population growth rateWeight factors of (2);
the specific analysis process of analyzing the disease information corresponding to each region is as follows:
the number of cases and the transmission speed in each region are respectively recorded asAnd->Wherein->The corresponding numbers of the areas are indicated,substituting the calculation formula +.>Obtaining the disease condition evaluation coefficient corresponding to the disease condition information of each region>Wherein->、/>Respectively expressed as the number of standard cases and standard propagation speed corresponding to the preset region, < + >>、The weight factors are respectively expressed as the number of cases and the propagation speed in the region;
the medical resource information corresponding to each region is analyzed, and the specific analysis process is as follows:
the number of hospitals in each region,The number of doctors and the number of medical facilities are respectively recorded as、/>And->Wherein->Indicating the corresponding numbers of the areas, +.>Substituting the calculation formula +.>Obtaining medical resource evaluation coefficients corresponding to the medical resource information of each region>Wherein->、/>、/>Respectively expressed as the number of standard hospitals, the number of standard doctors and the number of standard medical facilities corresponding to the preset region,/for the preset region>、/>、/>Respectively representing the weight factors corresponding to the number of hospitals, doctors and medical facilities in the region;
vaccination analysis module: the method comprises the steps of carrying out pre-estimation analysis on vaccination conditions corresponding to each region according to personnel assessment coefficients, illness state assessment coefficients and medical resource assessment coefficients corresponding to each region, and further obtaining pre-estimation assessment coefficients corresponding to vaccination conditions of each region;
the pre-estimated analysis is carried out on the vaccination conditions corresponding to each region, and the specific analysis process is as follows;
personnel evaluation coefficients corresponding to personnel information of each regionDisease evaluation coefficient corresponding to disease information of each region>Medical resource evaluation coefficient corresponding to medical resource information +.>Substitution of the calculation formula +.>Obtaining estimated evaluation coefficients corresponding to vaccination conditions in each region>，/>、/>、/>Respectively setting weight factors corresponding to the personnel evaluation coefficient, the illness evaluation coefficient and the medical resource evaluation coefficient;
an estimated module of vaccination: the method comprises the steps of obtaining the estimated quantity of vaccinations in each region according to the estimated evaluation coefficients corresponding to vaccinations in each region;
the method for obtaining the estimated quantity of vaccinations in each region comprises the following specific obtaining process:
comparing the estimated evaluation coefficients corresponding to the vaccination conditions of each region with the set estimated evaluation coefficients corresponding to the vaccination conditions of the regions, so as to obtain the estimated quantity of vaccinations corresponding to the estimated evaluation coefficients of the vaccination conditions of each region, and further obtain the estimated quantity of vaccinations of each region;
inventory analysis and deployment module for vaccine: the method comprises the steps of calculating a difference value according to the estimated quantity of vaccinations in each region and the actual quantity of vaccine stock in the corresponding region, so as to obtain a difference value between the estimated quantity of vaccinations in each region and the actual quantity of vaccine stock in the corresponding region, and allocating the actual quantity of vaccine stock in each region;
the actual quantity of vaccine stock in each area is allocated, and the specific allocation process is as follows:
a1, calculating a difference value between the estimated quantity of vaccinations in each region and the actual quantity of vaccine stocks in the corresponding region, wherein the difference value is obtained by subtracting the actual quantity of vaccine stocks in the corresponding region from the estimated quantity of vaccinations in each region, so as to judge that the actual quantity of vaccine stocks in each region is too high or too low;
a2, when the actual number of vaccine stocks in each area is judged to be too large or too small, then the actual number of vaccine stocks in the judgment area is further blended to the area with too small actual number of vaccine stocks in the judgment area;
the acquisition module of the adverse reaction quantity: the method is used for collecting the number of the adverse reaction personnel corresponding to each type of vaccine, and further obtaining the number of the adverse reaction personnel corresponding to each type of vaccine;
analysis module of vaccine adverse reaction: the method is used for analyzing the number of the adverse reaction personnel corresponding to each type of vaccine according to the number of the adverse reaction personnel corresponding to each type of vaccine to obtain the occurrence rate of the number of the adverse reaction personnel corresponding to each type of vaccine, and further judging whether the adverse reaction of each type of vaccine is easy to occur;
early warning terminal: the method is used for carrying out early warning prompt when a certain type of vaccine is easy to cause adverse reaction.
2. The integrated processing system for multidimensional health data according to claim 1, wherein the number of adverse reaction personnel corresponding to each type of vaccine is analyzed, and the specific analysis process is as follows:
counting total number of vaccinators corresponding to each type of vaccine, and marking asCounting the number of adverse reaction people corresponding to various types of vaccines, and marking as +.>Wherein->Numbers representing the correspondence of the various types, +.>Substituting the calculation formula +.>The number incidence of adverse reaction personnel corresponding to various types of vaccines is obtained>。
3. The integrated processing system for multidimensional health data according to claim 2, wherein the specific judging process is as follows:
comparing the occurrence rate of the number of the untoward reaction personnel corresponding to each type of vaccine with the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine, judging that the type of vaccine is not easy to cause untoward reaction if the occurrence rate of the number of the untoward reaction personnel corresponding to a certain type of vaccine is smaller than or equal to the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine, and judging that the type of vaccine is easy to cause untoward reaction if the occurrence rate of the number of the untoward reaction personnel corresponding to a certain type of vaccine is larger than the occurrence rate of the number of the untoward reaction personnel corresponding to the preset standard vaccine.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311534606.9A CN117253577B (en) | 2023-11-17 | 2023-11-17 | Multidimensional health data integrated processing system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311534606.9A CN117253577B (en) | 2023-11-17 | 2023-11-17 | Multidimensional health data integrated processing system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117253577A CN117253577A (en) | 2023-12-19 |
| CN117253577B true CN117253577B (en) | 2024-03-12 |
Family
ID=89137282
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311534606.9A Active CN117253577B (en) | 2023-11-17 | 2023-11-17 | Multidimensional health data integrated processing system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117253577B (en) |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117476198B (en) * | 2023-12-26 | 2024-04-19 | 四川省大数据技术服务中心 | Large-scale medical detection information system for multiple scenes |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6208974B1 (en) * | 1997-12-30 | 2001-03-27 | Medical Management International, Inc. | Method and system for managing wellness plans for a medical care practice |
| CN110910152A (en) * | 2019-11-21 | 2020-03-24 | 济南大学 | Vaccine tracing and monitoring system and method |
| CN111798952A (en) * | 2020-07-16 | 2020-10-20 | 山东省玖玖医养健康产业有限公司 | Resident health management medical big data platform |
| CN112734153A (en) * | 2020-11-11 | 2021-04-30 | 重庆医科大学附属儿童医院 | Emergency resource allocation method, system and application in sudden public health event |
| CN113113147A (en) * | 2021-04-28 | 2021-07-13 | 哈尔滨工业大学 | Method for distributing hepatitis B vaccines with priority based on crowd heterogeneity |
| WO2022086854A1 (en) * | 2020-10-19 | 2022-04-28 | Camas Incorporated | Methods of using passive immunity to decrease transmission of infectious diseases |
| CN115547465A (en) * | 2022-05-15 | 2022-12-30 | 兰州大学 | Vaccine distribution system based on regional epidemic spread risk classification |
| CN116113430A (en) * | 2020-02-04 | 2023-05-12 | 奎尔法克股份有限公司 | Coronavirus vaccine |
| CN116779184A (en) * | 2023-04-17 | 2023-09-19 | 北京大学 | Method, system and equipment for quasi-real-time monitoring of vaccine safety and storage medium |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20220291011A1 (en) * | 2021-03-15 | 2022-09-15 | Here Global B.V. | Method and apparatus for providing navigation and location recommendation based on geospatial vaccination data |
-
2023
- 2023-11-17 CN CN202311534606.9A patent/CN117253577B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6208974B1 (en) * | 1997-12-30 | 2001-03-27 | Medical Management International, Inc. | Method and system for managing wellness plans for a medical care practice |
| CN110910152A (en) * | 2019-11-21 | 2020-03-24 | 济南大学 | Vaccine tracing and monitoring system and method |
| CN116113430A (en) * | 2020-02-04 | 2023-05-12 | 奎尔法克股份有限公司 | Coronavirus vaccine |
| CN111798952A (en) * | 2020-07-16 | 2020-10-20 | 山东省玖玖医养健康产业有限公司 | Resident health management medical big data platform |
| WO2022086854A1 (en) * | 2020-10-19 | 2022-04-28 | Camas Incorporated | Methods of using passive immunity to decrease transmission of infectious diseases |
| CN112734153A (en) * | 2020-11-11 | 2021-04-30 | 重庆医科大学附属儿童医院 | Emergency resource allocation method, system and application in sudden public health event |
| CN113113147A (en) * | 2021-04-28 | 2021-07-13 | 哈尔滨工业大学 | Method for distributing hepatitis B vaccines with priority based on crowd heterogeneity |
| CN115547465A (en) * | 2022-05-15 | 2022-12-30 | 兰州大学 | Vaccine distribution system based on regional epidemic spread risk classification |
| CN116779184A (en) * | 2023-04-17 | 2023-09-19 | 北京大学 | Method, system and equipment for quasi-real-time monitoring of vaccine safety and storage medium |
Non-Patent Citations (5)
| Title |
|---|
| 上海市2017-2019年人乳头瘤病毒疫苗接种率和疑似预防接种异常反应监测;刘捷宸;吴琳琳;白庆瑞;任佳;邵慧勇;黄卓英;;中国疫苗和免疫(03);第664-667页 * |
| 区域卫生信息平台的有效性评价指标体系构建;董雪;夏晨曦;;中华医学图书情报杂志;20170815(第08期);第17-24页 * |
| 疫苗全程溯源管理信息系统的设计与实现;李健思;方兴;闫肃;孙雪峰;姚文清;卢春明;杨佐森;;中国卫生信息管理杂志(03);第485-490页 * |
| 面向重大传染性疾病的应急资源管理研究综述;江志斌等;《工业工程》;20201202;第23卷(第6期);第1-9页 * |
| 黄热疫苗接种人群不良反应分析;于畅;张明;李云峰;吴刚;;中国国境卫生检疫杂志;20100225(第01期);第50-51+66页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117253577A (en) | 2023-12-19 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN117253577B (en) | Multidimensional health data integrated processing system | |
| Draper et al. | MBRRACE-UK | |
| CN110826908A (en) | Evaluation method and device for artificial intelligent prediction, storage medium and electronic equipment | |
| US20120158423A1 (en) | System and Method for Radiology Report Recall Monitoring | |
| JP2004507309A (en) | X-ray image quantitative analysis method and apparatus | |
| Dujardin et al. | The strategy of risk approach in antenatal care: evaluation of the referral compliance | |
| Harth et al. | Ossification degrees of cranial sutures determined with flat‐panel computed tomography: narrowing the age estimate with extrema | |
| US11392872B2 (en) | Optimizing workflows | |
| CN111695836A (en) | Clinical trial online operation management and control integrated system | |
| CN109522301A (en) | A kind of data processing method, electronic equipment and storage medium | |
| CN115240801A (en) | Medical satisfaction monitoring system and method based on intelligent questionnaire survey | |
| CN115185936A (en) | Medical clinical data quality analysis system based on big data | |
| CN110710986A (en) | CT image-based cerebral arteriovenous malformation detection method and system | |
| CN112735579A (en) | Rapid registration treatment system for emergency patients | |
| CN113113118A (en) | Remote film reading system and method | |
| Adeyi et al. | Essential obstetric care: assessment and determinants of quality | |
| CN116779184A (en) | Method, system and equipment for quasi-real-time monitoring of vaccine safety and storage medium | |
| Gonzalez et al. | Frontonasal Fold Thickness–to–Nasal Bone Length Ratio as a Prenatal Sonographic Marker for Trisomy 21 in a Low‐Risk Population | |
| CN114999644A (en) | Building personnel epidemic situation prevention and control visual management system and management method | |
| US20200411172A1 (en) | Integrated value based care return on investment system | |
| CN110223760B (en) | Medical image information acquisition and fusion method and system | |
| Graham et al. | Measuring and estimating maternal mortality in the era of HIV/AIDS | |
| CN112509659A (en) | Medical insurance and death cause monitoring data-based tumor patient survival monitoring method and device | |
| Parker et al. | Data quality: How the flow of data influences data quality in a small to medium medical practice | |
| Rim et al. | Prevalence of anal cytology screening among persons with HIV and lack of access to high-resolution anoscopy at HIV care facilities |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |