CN103310104A - Drug resistance monitoring system for bacteria - Google Patents
Drug resistance monitoring system for bacteria Download PDFInfo
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- CN103310104A CN103310104A CN2013102354769A CN201310235476A CN103310104A CN 103310104 A CN103310104 A CN 103310104A CN 2013102354769 A CN2013102354769 A CN 2013102354769A CN 201310235476 A CN201310235476 A CN 201310235476A CN 103310104 A CN103310104 A CN 103310104A
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Abstract
The invention discloses a drug resistance monitoring system for bacteria. On the basis of whonet software development, data are collected and analyzed with an Internet technology; local version data in a whonet format are uploaded to a server by using an uploading client side; the server is provided with a web monitoring data analyzing system; data are analyzed, and outbreak of drug-resistance bacteria is monitored in real time; and the information is fed back to a user in a pre-warning manner. The drug resistance monitoring system for the bacteria can realize real-time data acquisition, transmission and intelligent analysis of monitoring of important drug-resistance bacteria, solves the problem of promptness of drug-resistance bacterium infection monitoring in hospitals, and improves a relevant information database of multiple resistant bacteria; and a system for monitoring multiple resistant bacteria and infection of the multiple resistant bacteria in real time and pre-warning the outbreak of the drug-resistance bacteria rapidly is established.
Description
Technical field
The present invention relates to a kind of important drug-fast bacteria monitoring real-time data acquisition, transmission, intelligent analysis technology, and counterweight drug-fast bacteria and infection thereof carry out the system that Real Time Monitoring and drug-fast bacteria break out quick early warning, can be applicable to hospital, Disease Control and Prevention Center and related medical mechanism to the Real Time Monitoring of drug-resistant bacteria.
Background technology
At present, the operating process of the most bacterial resistance monitoring in the whole world all based on the typing of Microbiological Lab's experimental result, the standardization of data (using the whonet invention), with mode reported data, the central database data administrator of Email data are put in order per month and gather, the examining and the feedback of analysis, data message of data.But monitoring needs a large amount of manpowers that data are processed, analyzed, and can not accomplish Real-Time Monitoring, early warning and timely feedback information, can not feed back in the very first time wrong or special data simultaneously.As previously mentioned, present monitoring net data only can be used for the resistance analysis of medical institutions, and can't accomplish Real-Time Monitoring and early warning.
Summary of the invention
Can't Real-Time Monitoring at present general bacterial resistance monitoring net institute, early warning, need simultaneously the deficiencies such as certain specialty analysis personnel, the invention provides a kind of bacterial resistance monitoring system, this system is uploaded bacterial resistance information in real time by data client, realize Direct Network Reporting System, data audit robotization, automatic feedback and automatic analysis data system, can not only real-time analysis drug-resistant bacteria data, timely early warning information is provided, simultaneously can make things convenient for medical institutions to this hospital, the Real-Time Monitoring of the bacterial resistances such as area, in time understand the bacterial resistance change and progress in associated mechanisms and area, provide foundation for formulating relevant countermeasure.
The technical solution adopted for the present invention to solve the technical problems is:
A kind of bacterial resistance monitoring system, based on the whonet software development, utilize Internet technology to collect, analyze data, the whonet formatted data of city edition, utilization is uploaded client upload to server, server has web Analysis on monitoring data system, to the outburst of data analysis, Real Time Monitoring drug-fast bacteria, and with the form feedback user of early warning.
The described client of uploading is to the judgement of whonet formatted data at the audit of submitting requirement, form to and invalid data, to form and or the invalid data data that do not reach requirement return; Bacterial resistance situation data upload after the timely feedback user of described web Analysis on monitoring data system to existing in the data carries out data to the field of setting simultaneously and gathers, analyzes, with the form real-time online demonstration of form; Described data analysis displaying contents comprises bacterium distribution plan, bacterial drug resistance statistics, a situation arises for methicillin-resistant staphylococcus aureus, methicillin-resistant Staphylococcus resistance statistics, MSSA resistance statistics, Production by Bacteria ESBL situation and produce 7 modules of ESBL bacterial resistance statistics; Real Time Monitoring, the pre-alarming system of described web Analysis on monitoring data system comprises the appearance of special drug-fast bacteria and Analysis on monitoring data particular case.
Judging of the audit of described form and invalid data comprises that call format is the whonet formatted data; The judgement of invalid data comprises the antibody-resistant bacterium that Mandatory fields is imperfect and special; Required item does not complete and wholely refers in sample type (numeral), species of samples, the bacteria name that either field is not filled in and then be considered as invalid and return; For all records of once uploading, age or date of birth, medical record number, section office, sample date, bacteria types (G+/G-) field accumulative total 10% or above not filling out are then return; Special resistance situation comprises the staphylococcus to vancomycin intermediary or resistance, staphylococcus to teicoplanin intermediary or resistance, staphylococcus to Linezolid intermediary or resistance, Streptococcus hemolyticus to penicillin or third-generation cephalosporin resistance, streptococcus bacterium to drug resistance of vancomycin, to the insensitive haemophilus influenzae of third-generation cephalosporin, to Meropenem, the insensitive NEISSERIA GONORRHOEAE of Imipenem, to the insensitive Neisseria meningitidis of third-generation cephalosporin, to haemophilus influenzae, moraxelle catarrhalis does not detect beta lactamase, to Meropenem, the insensitive Escherichia coli of Imipenem, to the insensitive Neisseria meningitidis of minocycline; To such situation, uploading data can be refused by system, requires data are checked, and points out.
The special drug-fast bacteria of described web Analysis on monitoring data system and the appearance of Analysis on monitoring data particular case comprise:
1) to the staphylococcus of vancomycin intermediary or resistance, staphylococcus to teicoplanin intermediary or resistance, staphylococcus to Linezolid intermediary or resistance, Streptococcus hemolyticus to penicillin or third-generation cephalosporin resistance, streptococcus bacterium to drug resistance of vancomycin, to the insensitive haemophilus influenzae of third-generation cephalosporin, to the insensitive NEISSERIA GONORRHOEAE of Meropenem/Imipenem, to third-generation cephalosporin or the insensitive Neisseria meningitidis of minocycline with to the insensitive Escherichia coli of Carbapenems;
2) front and back 2 season resistance situation greatly changes: comprise that colibacillus increases by 1 times to the resistant rate of Imipenem than the last quarter, colibacillus increases by 1 times to the resistant rate of Meropenem than the last quarter, Klebsiella Pneumoniae increases by 1 times to the resistant rate of Imipenem than the last quarter, Klebsiella Pneumoniae increases by 1 times to the resistant rate of Meropenem than the last quarter, enterococcus increases by 1 times to the resistant rate of vancomycin than increasing by 1 times and the enterococcus resistant rate to Linezolid last quarter than the last quarter;
3) similar difference exists unusual: comprise Escherichia coli to Ciprofloxacin and lavo-ofloxacin resistant rate difference surpass 30% and Klebsiella Pneumoniae to the resistant rate difference of Meropenem and Imipenem above 5%;
4) the main target Bacterial Drug Resistance of Patients is unusual: comprise that enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the ceftriaxone resistant rate; Enterobacteriaceae lactobacteriaceae Cefotaxime resistant rate surpasses 30%, 40%, 50%, 75%; Enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the ciprofloxacin resistance rate; Enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the lavo-ofloxacin resistant rate; Pseudomonas aeruginosa surpasses 30%, 40%, 50%, 75% to the imipenem-resistant rate; Pseudomonas aeruginosa surpasses 30%, 40%, 50%, 75% to the Meropenem resistant rate; Acinetobacter bauamnnii to the imipenem-resistant rate surpass 30%, 40%, 50%, 75% and Acinetobacter bauamnnii the Meropenem resistant rate is surpassed 30%, 40%, 50%, 75%.
Described data upload client is connected Internet technology with web Analysis on monitoring data system and is connected.
Described server is remote server or home server.
Described remote server is Cloud Server.
The invention has the beneficial effects as follows: can realize important drug-fast bacteria monitoring real-time data acquisition, transmission, intelligent analysis, solve the promptness problem of drug-fast bacteria monitoring of hospital infection, improve multi-drug resistant bacteria relevant information data storehouse; Set up multi-drug resistant bacteria and infection Real Time Monitoring thereof and drug-fast bacteria and break out quick pre-alarming system.
Description of drawings
The present invention is further described below in conjunction with drawings and Examples.
Fig. 1 is that the client data of uploading of the present invention is uploaded process flow diagram.
Fig. 2 is the data results display interface of web Analysis on monitoring data of the present invention system.
Embodiment
As shown in Figure 1, to client, set data and submitted rule to, simultaneity factor can be examined submitting data to, the information such as reason, label of uploading mistake and uploading failure not conforming to the Notes of Key Data of submitting rule to.If have the information that does not meet auditing standards in the data of uploading for the 1st time, then can not successfully upload; Can in " invalid data " frame, check the reason of uploading failure, or click " derivation invalid data ", check accordingly raw data, if really wrong, can in raw data, make amendment, and then upload, then can successfully upload by audit, if still wrong, but upload after 24 hours again at the interval.
The judgement of invalid data comprises the antibody-resistant bacterium that Mandatory fields is imperfect and special.Required item does not complete and wholely refers in sample type (numeral), species of samples, the bacteria name that either field is not filled in and then be considered as invalid and return; For all records of once uploading, the fields such as age or date of birth, medical record number, section office, sample date, bacteria types (G+/G-) accumulative total 10% or above not filling out are then return.Special resistance situation comprises the staphylococcus to vancomycin intermediary or resistance, staphylococcus to teicoplanin intermediary or resistance, staphylococcus to Linezolid intermediary or resistance, Streptococcus hemolyticus to penicillin or third-generation cephalosporin resistance, streptococcus bacterium to drug resistance of vancomycin, to the insensitive haemophilus influenzae of third-generation cephalosporin, to Meropenem, the insensitive NEISSERIA GONORRHOEAE of Imipenem, to the insensitive Neisseria meningitidis of third-generation cephalosporin, to haemophilus influenzae, moraxelle catarrhalis does not detect beta lactamase, to Meropenem, the insensitive Escherichia coli of Imipenem, to the insensitive Neisseria meningitidis of minocycline.To such situation, uploading data can be refused by system, requires data are checked, and can point out such as " Gui Yuan finds the * strain to the staphylococcus of teicoplanin intermediary or resistance, please check to keep bacterial strain and send centralab ".
After data are successfully uploaded, 00:00 every day of system to next day 6:00 data are carried out analyzing and processing, if there are the resistance abnormal conditions in the data, after the data upload the 2nd day, system can be by mail reminder keepers at different levels and hospital, such as prompting " Gui Yuan finds the * strain to the staphylococcus of vancomycin intermediary or resistance, please check to keep bacterial strain and send centralab ".
As shown in Figure 2, in web Analysis on monitoring data system, at present on the one hand can be to bacterium distribution plan, bacterial drug resistance statistics, a situation arises for methicillin-resistant staphylococcus aureus, methicillin-resistant Staphylococcus resistance statistics, MSSA resistance statistics, Production by Bacteria ESBL situation and produce 7 aspects such as ESBL bacterial resistance statistics and show with the form of form; Set up simultaneously the early warning mechanism of drug-resistant bacteria, specifically comprise
1): comprise the staphylococcus to vancomycin intermediary or resistance, staphylococcus to teicoplanin intermediary or resistance, staphylococcus to Linezolid intermediary or resistance, Streptococcus hemolyticus to penicillin or third-generation cephalosporin resistance, streptococcus bacterium to drug resistance of vancomycin, to the insensitive haemophilus influenzae of third-generation cephalosporin, to the insensitive NEISSERIA GONORRHOEAE of Meropenem/Imipenem, to third-generation cephalosporin or the insensitive Neisseria meningitidis of minocycline with to the insensitive Escherichia coli of Carbapenems.
2) front and back 2 season resistance situation greatly changes: comprise that colibacillus increases by 1 times to the resistant rate of Imipenem than the last quarter, colibacillus increases by 1 times to the resistant rate of Meropenem than the last quarter, Klebsiella Pneumoniae increases by 1 times to the resistant rate of Imipenem than the last quarter, Klebsiella Pneumoniae increases by 1 times to the resistant rate of Meropenem than the last quarter, enterococcus increases by 1 times to the resistant rate of vancomycin than increasing by 1 times and the enterococcus resistant rate to Linezolid last quarter than the last quarter.
3) similar difference exists unusual: comprise Escherichia coli to Ciprofloxacin and lavo-ofloxacin resistant rate difference surpass 30% and Klebsiella Pneumoniae to the resistant rate difference of Meropenem and Imipenem above 5%.
4) the main target Bacterial Drug Resistance of Patients is unusual: comprise that enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the ceftriaxone resistant rate; Enterobacteriaceae lactobacteriaceae Cefotaxime resistant rate surpasses 30%, 40%, 50%, 75%; Enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the ciprofloxacin resistance rate; Enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the lavo-ofloxacin resistant rate; Pseudomonas aeruginosa surpasses 30%, 40%, 50%, 75% to the imipenem-resistant rate; Pseudomonas aeruginosa surpasses 30%, 40%, 50%, 75% to the Meropenem resistant rate; Acinetobacter bauamnnii to the imipenem-resistant rate surpass 30%, 40%, 50%, 75% and Acinetobacter bauamnnii the Meropenem resistant rate is surpassed 30%, 40%, 50%, 75%.
Claims (7)
1. bacterial resistance monitoring system, based on the whonet software development, utilize Internet technology to collect, analyze data, it is characterized in that: the whonet formatted data of city edition, utilization is uploaded client upload to server, server has web Analysis on monitoring data system, to the outburst of data analysis, Real Time Monitoring drug-fast bacteria, and with the form feedback user of early warning.
2. bacterial resistance monitoring system according to claim 1, it is characterized in that: the described client of uploading is to the judgement of whonet formatted data at the audit of submitting requirement, form to and invalid data, to form and or the invalid data data that do not reach requirement return; Bacterial resistance situation data upload after the timely feedback user of described web Analysis on monitoring data system to existing in the data carries out data to the field of setting simultaneously and gathers, analyzes, with the form real-time online demonstration of form; Described data analysis displaying contents comprises bacterium distribution plan, bacterial drug resistance statistics, a situation arises for methicillin-resistant staphylococcus aureus, methicillin-resistant Staphylococcus resistance statistics, MSSA resistance statistics, Production by Bacteria ESBL situation and produce 7 modules of ESBL bacterial resistance statistics; Real Time Monitoring, the pre-alarming system of described web Analysis on monitoring data system comprises the appearance of special drug-fast bacteria and Analysis on monitoring data particular case.
3. bacterial resistance monitoring system according to claim 2, it is characterized in that: judging of the audit of described form and invalid data comprises that call format is the whonet formatted data; The judgement of invalid data comprises the antibody-resistant bacterium that Mandatory fields is imperfect and special; Required item does not complete and wholely refers in sample type (numeral), species of samples, the bacteria name that either field is not filled in and then be considered as invalid and return; For all records of once uploading, age or date of birth, medical record number, section office, sample date, bacteria types (G+/G-) field accumulative total 10% or above not filling out are then return; Special resistance situation comprises the staphylococcus to vancomycin intermediary or resistance, staphylococcus to teicoplanin intermediary or resistance, staphylococcus to Linezolid intermediary or resistance, Streptococcus hemolyticus to penicillin or third-generation cephalosporin resistance, streptococcus bacterium to drug resistance of vancomycin, to the insensitive haemophilus influenzae of third-generation cephalosporin, to Meropenem, the insensitive NEISSERIA GONORRHOEAE of Imipenem, to the insensitive Neisseria meningitidis of third-generation cephalosporin, to haemophilus influenzae, moraxelle catarrhalis does not detect beta lactamase, to Meropenem, the insensitive Escherichia coli of Imipenem, to the insensitive Neisseria meningitidis of minocycline; To such situation, uploading data can be refused by system, requires data are checked, and points out.
4. bacterial resistance monitoring system according to claim 2 is characterized in that: the special drug-fast bacteria of described web Analysis on monitoring data system and the appearance of Analysis on monitoring data particular case comprise:
1) to the staphylococcus of vancomycin intermediary or resistance, staphylococcus to teicoplanin intermediary or resistance, staphylococcus to Linezolid intermediary or resistance, Streptococcus hemolyticus to penicillin or third-generation cephalosporin resistance, streptococcus bacterium to drug resistance of vancomycin, to the insensitive haemophilus influenzae of third-generation cephalosporin, to the insensitive NEISSERIA GONORRHOEAE of Meropenem/Imipenem, to third-generation cephalosporin or the insensitive Neisseria meningitidis of minocycline with to the insensitive Escherichia coli of Carbapenems;
2) front and back 2 season resistance situation greatly changes: comprise that colibacillus increases by 1 times to the resistant rate of Imipenem than the last quarter, colibacillus increases by 1 times to the resistant rate of Meropenem than the last quarter, Klebsiella Pneumoniae increases by 1 times to the resistant rate of Imipenem than the last quarter, Klebsiella Pneumoniae increases by 1 times to the resistant rate of Meropenem than the last quarter, enterococcus increases by 1 times to the resistant rate of vancomycin than increasing by 1 times and the enterococcus resistant rate to Linezolid last quarter than the last quarter;
3) similar difference exists unusual: comprise Escherichia coli to Ciprofloxacin and lavo-ofloxacin resistant rate difference surpass 30% and Klebsiella Pneumoniae to the resistant rate difference of Meropenem and Imipenem above 5%;
4) the main target Bacterial Drug Resistance of Patients is unusual: comprise that enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the ceftriaxone resistant rate; Enterobacteriaceae lactobacteriaceae Cefotaxime resistant rate surpasses 30%, 40%, 50%, 75%; Enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the ciprofloxacin resistance rate; Enterobacteriaceae lactobacteriaceae surpasses 30%, 40%, 50%, 75% to the lavo-ofloxacin resistant rate; Pseudomonas aeruginosa surpasses 30%, 40%, 50%, 75% to the imipenem-resistant rate; Pseudomonas aeruginosa surpasses 30%, 40%, 50%, 75% to the Meropenem resistant rate; Acinetobacter bauamnnii to the imipenem-resistant rate surpass 30%, 40%, 50%, 75% and Acinetobacter bauamnnii the Meropenem resistant rate is surpassed 30%, 40%, 50%, 75%.
5. bacterial resistance monitoring system according to claim 1 is characterized in that: the described client of uploading is connected Internet technology with web Analysis on monitoring data system and is connected.
6. bacterial resistance monitoring system according to claim 1, it is characterized in that: described server is remote server or home server.
7. bacterial resistance monitoring system according to claim 6, it is characterized in that: described remote server is Cloud Server.
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CN107545138A (en) * | 2017-08-24 | 2018-01-05 | 惠州市阳光生物科技有限公司 | Microorganism detection method, microbial detection device, computer-readable recording medium and microorganism detection system based on big data |
CN110923230A (en) * | 2019-11-07 | 2020-03-27 | 浙江大学 | sgRNA sequence for targeted knockout of blaNDM-1 gene and application thereof |
CN112542249A (en) * | 2020-11-13 | 2021-03-23 | 杭州杏林信息科技有限公司 | Method and device for synchronously detecting times of multiple drug resistance cases based on MapReduce and big data statistics |
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CN114774262A (en) * | 2022-06-21 | 2022-07-22 | 山东省饲料兽药质量检验中心 | Animal source bacterium drug resistance monitoring traceability system |
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Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
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CN112582042A (en) * | 2020-11-13 | 2021-03-30 | 杭州杏林信息科技有限公司 | Method and system for synchronously detecting times of infected multi-drug-resistant bacteria cases based on MapReduce and big data management |
CN114774262A (en) * | 2022-06-21 | 2022-07-22 | 山东省饲料兽药质量检验中心 | Animal source bacterium drug resistance monitoring traceability system |
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