CN111223573A - Hospital infection monitoring management method and system - Google Patents
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- 208000015181 infectious disease Diseases 0.000 claims abstract description 71
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- 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
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Abstract
The invention discloses a hospital infection monitoring and management method, which comprises the following steps: acquiring disease condition diagnosis data and operation treatment data of a patient, and acquiring body temperature data of the patient in real time; according to the disease condition diagnosis data and the body temperature data, judging and analyzing by combining a preset disease susceptibility characteristic rule, and screening to obtain information of suspected nosocomial patients; performing statistical analysis of morbidity time periods on all suspected nosocomial patient information obtained by screening to obtain morbidity analysis results of each time period; calculating infection morbidity in each surgical operation according to the surgical treatment data statistics, and analyzing the infection morbidity to obtain an operation infection morbidity analysis result; and receiving the morbidity analysis result of each time period and the surgical infection morbidity analysis result, and generating a working report according to the morbidity analysis result and the surgical infection morbidity analysis result.
Description
Technical Field
The invention relates to the field of nosocomial feelings monitoring, in particular to a nosocomial feelings monitoring management method and a nosocomial feelings monitoring management system.
Background
The hospital infection data refers to data of nosocomial diseases, and is used for counting the numerical values of the nosocomial diseases so as to prevent the patients from being harmed due to the infectious diseases. In order to ensure the life safety of the patient, the hospital feeling data needs to be managed and analyzed. The existing hospital monitoring and management method is to manually record through medical care personnel and obtain corresponding analysis results through the judgment of the state of an illness by a doctor. The manual monitoring management mode cannot be analyzed in time due to the fact that the number of patients is increased day by day, and the timeliness of missed medical data caused by low manual analysis efficiency leads the life safety of the patients to be threatened.
Disclosure of Invention
The invention provides a hospital infection monitoring management method and system, which can solve the technical problem that medical data timeliness is missed due to low manual analysis efficiency caused by increasing number of patients in the conventional manual monitoring management mode through automatically screening suspected hospital infection patient information, carrying out statistical analysis and generating a report, thereby improving the disease analysis efficiency, ensuring the timeliness of disease data and further ensuring the life safety of patients.
In order to solve the technical problem, an embodiment of the present invention provides a hospital infection monitoring and management method, including:
acquiring disease condition diagnosis data and operation treatment data of a patient, and acquiring body temperature data of the patient in real time;
according to the disease condition diagnosis data and the body temperature data, judging and analyzing by combining a preset disease susceptibility characteristic rule, and screening to obtain information of suspected nosocomial patients;
performing statistical analysis of morbidity time periods on all suspected nosocomial patient information obtained by screening to obtain morbidity analysis results of each time period;
calculating infection morbidity in each surgical operation according to the surgical treatment data statistics, and analyzing the infection morbidity to obtain an operation infection morbidity analysis result;
receiving the morbidity analysis result of each time period and the operation infection morbidity analysis result, and generating a work report according to the morbidity analysis result and the operation infection morbidity analysis result;
wherein the step of analyzing the incidence of infection specifically comprises: according to the disease analysis result of each time period, acquiring mobile phone traffic data and relevant base station data of an infected and diseased patient in a time period before and after the disease; and performing track visualization analysis on the mobile phone traffic data and the related base station data on a geographic information system platform to obtain an operation infection morbidity analysis result.
Preferably, the work report is displayed in a graphical table form.
Preferably, the display content of the working report comprises ICU hospital morbidity and neonatal hospital morbidity.
As a preferred scheme, the statistical analysis of the morbidity time period of all the suspected nosocomial patient information obtained by screening includes identifying the characteristics of multiple drug-resistant bacteria patients and extracting the patient information with the characteristics of multiple drug-resistant bacteria, so that medical staff can further determine the infected parts and infected areas of the patients.
As a preferable scheme, the hospital infection monitoring and management method further comprises the following steps: and judging the morbidity analysis result of each time period and the operation infection morbidity analysis result, and triggering an early warning instruction when judging that an abnormal morbidity condition occurs so as to enable the server to send an alarm signal.
The embodiment of the invention also provides a hospital infection monitoring and management system, which comprises:
the data acquisition module is used for acquiring disease condition diagnosis data and operation treatment data of a patient and acquiring body temperature data of the patient in real time;
the judgment analysis module is used for carrying out judgment analysis according to the disease condition diagnosis data and the body temperature data by combining a preset disease feeling characteristic rule, and screening to obtain information of suspected nosocomial patients;
the statistical analysis module is used for performing statistical analysis of morbidity time periods on all the screened suspected nosocomial patient information to obtain morbidity analysis results of each time period;
the statistical calculation module is used for statistically calculating the infection morbidity in each surgical operation according to the surgical treatment data and analyzing the infection morbidity to obtain an operation infection morbidity analysis result;
the report generation module is used for receiving the morbidity analysis result of each time period and the surgical infection morbidity analysis result and generating a working report according to the morbidity analysis result and the surgical infection morbidity analysis result;
wherein the step of analyzing the incidence of infection specifically comprises: according to the disease analysis result of each time period, acquiring mobile phone traffic data and relevant base station data of an infected and diseased patient in a time period before and after the disease; and performing track visualization analysis on the mobile phone traffic data and the related base station data on a geographic information system platform to obtain an operation infection morbidity analysis result.
Preferably, the statistical analysis module is further configured to: the characteristics of the multiple drug-resistant bacteria are identified, and the patient information with the characteristics of the multiple drug-resistant bacteria is extracted, so that medical staff can further determine the infected part and the infected area of the patient.
As a preferred scheme, the hospital monitoring management system further comprises: and the abnormity early warning module is used for judging the morbidity analysis result of each time period and the operation infection morbidity analysis result, and triggering an early warning instruction when judging that an abnormal morbidity condition occurs so as to enable the server to send an alarm signal.
Compared with the prior art, the embodiment of the invention has the following beneficial effects:
according to the method, the suspected nosocomial patient information is automatically screened, statistical analysis is carried out, and a report is generated, so that the technical problem that medical data timeliness is missed due to low manual analysis efficiency caused by increasing number of patients in the conventional manual monitoring and management mode is solved, the morbidity analysis efficiency is improved, the timeliness of the morbidity data is guaranteed, and further the life safety of the patient is guaranteed.
Drawings
FIG. 1: the steps of the hospital monitoring and managing method in the embodiment of the invention are a flow chart;
FIG. 2: the structural schematic diagram of the hospital monitoring management system in the embodiment of the invention is shown.
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, a preferred embodiment of the present invention provides a hospital monitoring and managing method, including:
s1, acquiring disease diagnosis data and operation treatment data of a patient, and acquiring body temperature data of the patient in real time;
through the correlation analysis and statistics of relevant patients, illness states, operation conditions and various infection morbidity data, doctors and managers are helped to know the nosocomial morbidity of each department of a hospital and various nosocomial morbidity, various important factors influencing or causing the nosocomial morbidity are found out, and objective data support is provided for formulating effective nosocomial control measures. Firstly, data acquisition is carried out on a plurality of medical systems through a crawler technology, wherein the data acquisition comprises disease condition diagnosis data and operation treatment data of a patient; specifically, the medical condition diagnosis data can be obtained by acquiring an electronic medical record of the patient, performing text recognition on the electronic medical record, and extracting the medical condition diagnosis data of the patient. Specifically, the surgical treatment data may be acquired via surgical device monitoring data or surgical treatment data in an electronic medical record. In order to detect physical signs of a patient, sign data of the patient, including body temperature data and the like, are obtained. The step can realize automatic detection and data acquisition through detection instruments arranged at each entrance and exit of the hospital, and can also directly carry out physical sign detection on the patient to acquire body temperature data of the patient. It should be noted that this embodiment is only one embodiment for acquiring the body temperature data of the patient, and is not intended to limit the technical scope of the present invention, and the body temperature data of the patient may be acquired through various ways based on the data acquisition technology of the present invention.
S2, according to the disease condition diagnosis data and the body temperature data, judging and analyzing by combining a preset disease feeling characteristic rule, and screening to obtain information of suspected nosocomial patients;
in order to grasp the nosocomial morbidity of each department, the suspected nosocomial patients need to be monitored. The method is characterized in that an infection characteristic rule is set in advance as a detection standard of the hospital infection diseases, the infection characteristic rule is established by doctors in departments of various hospitals according to data characteristics of the infection diseases, such as the cold diseases, the body temperature range rule of a patient is set to be more than 37 degrees, and when the body temperature of the patient is detected to be 38 degrees, the preset body temperature range rule of 37 degrees is already exceeded, the patient is judged to be a suspected cold patient. The method comprises the steps of setting disease data ranges of various diseases through disease characteristic rules preset by doctors, judging the disease of a patient by combining acquired disease diagnosis data and body temperature data, determining whether the patient belongs to suspected hospital-induced patients according to the set characteristic rules, and screening and extracting the information of the patient determined to be suspected hospital-induced patients.
S3, performing statistical analysis of morbidity time periods on all suspected nosocomial patient information obtained by screening to obtain morbidity analysis results of each time period;
in order to understand the disease onset time characteristics of the patients and to enable hospitals to find out important factors influencing or causing hospital sickness, the step is used for carrying out statistical analysis on the disease onset time of suspected hospital sick. And extracting and identifying the detection data of the suspected nosocomial patient from the screened suspected nosocomial patient information to obtain the morbidity time of the suspected nosocomial patient. And similarly, carrying out statistical analysis on the morbidity time of all the screened suspected hospital-induced patients to obtain the morbidity time period of all the suspected hospital-induced patients. In addition, statistics is carried out on disease data of each suspected hospital-infected patient, and disease analysis results of each time period are obtained by integrating the disease time periods of the suspected hospital-infected patients.
S4, calculating infection morbidity in each surgical operation according to the surgical treatment data statistics, and analyzing the infection morbidity to obtain an operation infection morbidity analysis result;
wherein the step of analyzing the incidence of infection specifically comprises: according to the disease analysis result of each time period, acquiring mobile phone traffic data and relevant base station data of an infected and diseased patient in a time period before and after the disease; and performing track visualization analysis on the mobile phone traffic data and the related base station data on a geographic information system platform to obtain an operation infection morbidity analysis result.
The statistical analysis of the incidence of nosocomial infections associated with each surgical procedure is also an important analysis point in the present technical solution. The step is to perform statistical analysis on the operation treatment data acquired in the step, wherein the number of infected patients is counted through the operation information of the patients and the infection data of the patients recorded in the operation treatment data. Patients with surgical hair coloring can be classified as having pre-operative patient infections, intra-operative patient infections, and post-operative patient infections. The infection time of the patient is determined according to the infection data of the patient recorded in the operation treatment information, and the infection incidence rate in each surgical operation is calculated through classification statistics. After the infection incidence is obtained, the data characteristics of the infection incidence are analyzed, including the dimensional factors of incidence quantity, incidence time, operation centralization and the like are subjected to statistical analysis, and the analysis result of the infection incidence with the operation can be obtained.
Further, tracks of infection morbidity patients in a period of time before and after morbidity are tracked by using a mobile phone track, and a trend that the patients are likely to send infection epidemics is judged; the mobile phone track of the infected person is combined with a geographic information system, so that the passing area and the environment condition of the infected person can be judged quickly and accurately, high-risk areas and crowds can be determined, and prevention and control measures can be taken timely.
And S5, receiving the morbidity analysis result of each time period and the surgical infection morbidity analysis result, and generating a working report according to the morbidity analysis result and the surgical infection morbidity analysis result. In this embodiment, the work report is displayed in a graphical form. In this embodiment, the display content of the work report includes the hospital morbidity situation of the ICU and the hospital morbidity situation of the newborn.
In order to more vividly display the analysis result data, the step can also generate a corresponding detection analysis report according to the obtained analysis result and a preset report rule, and upload the report to a server for storage so as to provide evidence for the later reference evaluation work. Further, in order to make the visualization display effect more vivid, the embodiment also graphically displays the form of the report.
In order to more intuitively highlight individual important influence factors, such as the ICU hospital morbidity situation and the neonatal hospital morbidity situation, the relevant data of the ICU hospital morbidity situation and the neonatal hospital morbidity situation are displayed in the working report in an emphasis manner.
According to the method, the suspected nosocomial patient information is automatically screened, statistical analysis is carried out, and a report is generated, so that the technical problem that medical data timeliness is missed due to low manual analysis efficiency caused by increasing number of patients in the conventional manual monitoring and management mode is solved, the morbidity analysis efficiency is improved, the timeliness of the morbidity data is guaranteed, and further the life safety of the patient is guaranteed.
In another embodiment, the statistical analysis of the morbidity time period of all the suspected nosocomial patient information obtained by screening includes identifying the characteristics of the multiple drug-resistant bacteria patients, and extracting the patient information with the characteristics of the multiple drug-resistant bacteria, so that the medical staff can further determine the infected part and the infected area of the patient.
Multidrug-resistant bacteria (MDROS), also known as multidrug-resistant microorganisms, occur as a result of bacterial mutation and overuse of antibacterial agents. Multiple drug resistance has many different definitions and often causes confusion. In technical guidelines for prevention and control of infection in multiple drug-resistant bacteria hospitals (trial) issued by the ministry of health in 2011, it is specifically indicated that multiple drug-resistant bacteria refer to bacteria that exhibit resistance to 3 or more types of antibacterial drugs used clinically. The occurrence of multiple drug-resistant bacteria (MDROS) is the result of bacterial variation and overuse of antibacterial drugs, MDROS infected patients often have complicated conditions and difficult cure, need to be treated by higher-level antibacterial drugs, and are easy to form colonized bacteria, thus causing heavy economic burden to the patients. And MDROS can be in contact with and spread through contaminated hands, articles and the like, so that hospital infection is easily caused, the pain of a patient is increased, the hospitalization date of the patient is prolonged, the medical cost is increased, and even death is caused. Therefore, the promotion of MDROS hospital infection prevention and control has great significance, the MDROS hospital infection can be reduced, the pain, death and economic burden of a patient can be relieved, and the medical quality and the hospital benefit can be improved. In addition, practice also proves that the occurrence of MDROS nosocomial infection can be effectively reduced by adopting intervention measures. Therefore, the technical scheme also performs key identification on the characteristics of the multiple drug-resistant bacteria patient, specifically, a characteristic rule for identifying the multiple drug-resistant bacteria is formulated for the characteristics of the multiple drug-resistant bacteria patient in a pre-established susceptibility characteristic rule, and the characteristic rule is identified. When a multi-drug-resistant bacterium patient is identified, the patient information is identified and extracted, so that medical staff can further determine the infected part and the infected area of the patient.
In another embodiment, the hospital monitoring and managing method further includes: and judging the morbidity analysis result of each time period and the operation infection morbidity analysis result, and triggering an early warning instruction when judging that an abnormal morbidity condition occurs so as to enable the server to send an alarm signal.
The abnormal morbidity condition is judged, and the nosocomial disease condition can be better monitored and managed. Firstly, data identification is carried out on the disease analysis results of each time period and the operation infection disease analysis results obtained in the steps, comparison is carried out according to a preset early warning data range, and when the abnormal disease condition is confirmed, an early warning instruction is triggered to enable medical staff to carry out necessary monitoring management.
Accordingly, referring to fig. 2, an embodiment of the present invention further provides a hospital monitoring management system, including:
the data acquisition module is used for acquiring disease condition diagnosis data and operation treatment data of a patient and acquiring body temperature data of the patient in real time;
the judgment analysis module is used for carrying out judgment analysis according to the disease condition diagnosis data and the body temperature data by combining a preset disease feeling characteristic rule, and screening to obtain information of suspected nosocomial patients;
the statistical analysis module is used for performing statistical analysis of morbidity time periods on all the screened suspected nosocomial patient information to obtain morbidity analysis results of each time period;
the statistical calculation module is used for statistically calculating the infection morbidity in each surgical operation according to the surgical treatment data and analyzing the infection morbidity to obtain an operation infection morbidity analysis result;
the report generation module is used for receiving the morbidity analysis result of each time period and the surgical infection morbidity analysis result and generating a working report according to the morbidity analysis result and the surgical infection morbidity analysis result;
wherein the step of analyzing the incidence of infection specifically comprises: according to the disease analysis result of each time period, acquiring mobile phone traffic data and relevant base station data of an infected and diseased patient in a time period before and after the disease; and performing track visualization analysis on the mobile phone traffic data and the related base station data on a geographic information system platform to obtain an operation infection morbidity analysis result.
In another embodiment, the statistical analysis module is further configured to: the characteristics of the multiple drug-resistant bacteria are identified, and the patient information with the characteristics of the multiple drug-resistant bacteria is extracted, so that medical staff can further determine the infected part and the infected area of the patient.
In another embodiment, the hospital monitoring management system further comprises: and the abnormity early warning module is used for judging the morbidity analysis result of each time period and the operation infection morbidity analysis result, and triggering an early warning instruction when judging that an abnormal morbidity condition occurs so as to enable the server to send an alarm signal.
An embodiment of the present invention further provides a computer-readable storage medium, where the computer-readable storage medium includes a stored computer program; wherein the computer program controls, when running, the device where the computer-readable storage medium is located to execute the hospital infection monitoring management method according to any of the above embodiments.
The embodiment of the present invention further provides a terminal device, where the terminal device includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, and the processor implements the hospital admission monitoring management method according to any of the above embodiments when executing the computer program.
Preferably, the computer program may be divided into one or more modules/units (e.g., computer program) that are stored in the memory and executed by the processor to implement the invention. The one or more modules/units may be a series of computer program instruction segments capable of performing specific functions, which are used for describing the execution process of the computer program in the terminal device.
The Processor may be a Central Processing Unit (CPU), other general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, etc., the general purpose Processor may be a microprocessor, or the Processor may be any conventional Processor, the Processor is a control center of the terminal device, and various interfaces and lines are used to connect various parts of the terminal device.
The memory mainly includes a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function, and the like, and the data storage area may store related data and the like. In addition, the memory may be a high speed random access memory, may also be a non-volatile memory, such as a plug-in hard disk, a Smart Memory Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like, or may also be other volatile solid state memory devices.
It should be noted that the terminal device may include, but is not limited to, a processor and a memory, and those skilled in the art will understand that the terminal device is only an example and does not constitute a limitation of the terminal device, and may include more or less components, or combine some components, or different components.
The above-mentioned embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, and it should be understood that the above-mentioned embodiments are only examples of the present invention and are not intended to limit the scope of the present invention. It should be understood that any modifications, equivalents, improvements and the like, which come within the spirit and principle of the invention, may occur to those skilled in the art and are intended to be included within the scope of the invention.
Claims (8)
1. A hospital monitoring and management method is characterized by comprising the following steps:
acquiring disease condition diagnosis data and operation treatment data of a patient, and acquiring body temperature data of the patient in real time;
according to the disease condition diagnosis data and the body temperature data, judging and analyzing by combining a preset disease susceptibility characteristic rule, and screening to obtain information of suspected nosocomial patients;
performing statistical analysis of morbidity time periods on all suspected nosocomial patient information obtained by screening to obtain morbidity analysis results of each time period;
calculating infection morbidity in each surgical operation according to the surgical treatment data statistics, and analyzing the infection morbidity to obtain an operation infection morbidity analysis result;
receiving the morbidity analysis result of each time period and the operation infection morbidity analysis result, and generating a work report according to the morbidity analysis result and the operation infection morbidity analysis result;
wherein the step of analyzing the incidence of infection specifically comprises: according to the disease analysis result of each time period, acquiring mobile phone traffic data and relevant base station data of an infected and diseased patient in a time period before and after the disease; and performing track visualization analysis on the mobile phone traffic data and the related base station data on a geographic information system platform to obtain an operation infection morbidity analysis result.
2. The hospital admissions monitoring and management method of claim 1, wherein said work report is presented in a graphical table.
3. The hospital admission monitoring and management method according to claim 2, wherein the display content of the working report includes ICU hospital admission incidence condition and neonatal hospital admission incidence condition.
4. The nosocomial monitoring and management method of claim 1, wherein the statistical analysis of the disease period of all suspected nosocomial patient information obtained by screening comprises identifying the characteristics of multiple drug-resistant bacteria patients, and extracting the patient information with the characteristics of multiple drug-resistant bacteria, so that medical staff can further determine the infected part and the infected area of the patient.
5. The hospital monitoring and management method of claim 1, further comprising: and judging the morbidity analysis result of each time period and the operation infection morbidity analysis result, and triggering an early warning instruction when judging that an abnormal morbidity condition occurs so as to enable the server to send an alarm signal.
6. A hospital monitoring and management system, comprising:
the data acquisition module is used for acquiring disease condition diagnosis data and operation treatment data of a patient and acquiring body temperature data of the patient in real time;
the judgment analysis module is used for carrying out judgment analysis according to the disease condition diagnosis data and the body temperature data by combining a preset disease feeling characteristic rule, and screening to obtain information of suspected nosocomial patients;
the statistical analysis module is used for performing statistical analysis of morbidity time periods on all the screened suspected nosocomial patient information to obtain morbidity analysis results of each time period;
the statistical calculation module is used for statistically calculating the infection morbidity in each surgical operation according to the surgical treatment data and analyzing the infection morbidity to obtain an operation infection morbidity analysis result;
the report generation module is used for receiving the morbidity analysis result of each time period and the surgical infection morbidity analysis result and generating a working report according to the morbidity analysis result and the surgical infection morbidity analysis result;
wherein the step of analyzing the incidence of infection specifically comprises: according to the disease analysis result of each time period, acquiring mobile phone traffic data and relevant base station data of an infected and diseased patient in a time period before and after the disease; and performing track visualization analysis on the mobile phone traffic data and the related base station data on a geographic information system platform to obtain an operation infection morbidity analysis result.
7. The hospital sensory monitoring management system of claim 6, wherein the statistical analysis module is further configured to: the characteristics of the multiple drug-resistant bacteria are identified, and the patient information with the characteristics of the multiple drug-resistant bacteria is extracted, so that medical staff can further determine the infected part and the infected area of the patient.
8. The hospital induction monitoring management system of claim 6, further comprising: and the abnormity early warning module is used for judging the morbidity analysis result of each time period and the operation infection morbidity analysis result, and triggering an early warning instruction when judging that an abnormal morbidity condition occurs so as to enable the server to send an alarm signal.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115691827A (en) * | 2023-01-04 | 2023-02-03 | 成都信通网易医疗科技发展有限公司 | Method and storage medium for determining suspected infected patient |
| CN115910374A (en) * | 2022-11-09 | 2023-04-04 | 杭州杏林信息科技有限公司 | Early warning method and medium for aggregation or outbreak time of hospital infectious diseases |
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| CN115691827A (en) * | 2023-01-04 | 2023-02-03 | 成都信通网易医疗科技发展有限公司 | Method and storage medium for determining suspected infected patient |
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