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Method and system for synchronously detecting number of cases infected with multi-drug-resistant bacteria based on MapReduce and big data management

A management method and management system technology, applied in patient-specific data, epidemiological alert system, drug reference, etc., can solve the problem of inability to evaluate the overall situation of nosocomial infection, inability to manage the number of multidrug-resistant bacterial cases, and inability to achieve multidrug-resistant nosocomial infection. Control and management of medicines and bacteria

Pending Publication Date: 2021-03-30
杭州杏林信息科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

That is to say, the existing management of hospital-acquired multi-drug-resistant bacteria cannot manage the number of cases of multi-drug-resistant bacteria. The overall prevention and control and management of hospital infection cannot be evaluated as a whole

Method used

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  • Method and system for synchronously detecting number of cases infected with multi-drug-resistant bacteria based on MapReduce and big data management
  • Method and system for synchronously detecting number of cases infected with multi-drug-resistant bacteria based on MapReduce and big data management
  • Method and system for synchronously detecting number of cases infected with multi-drug-resistant bacteria based on MapReduce and big data management

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Embodiment 1

[0088] Such as Figure 1-9 As shown, this embodiment proposes a method based on MapReduce and big data management to detect the number of cases of multidrug-resistant bacteria infected at the same time, including the following steps:

[0089] S1. Obtain hospitalization process information A, transfer information B, bacterial culture information J, drug susceptibility test information K, selected statistical time, selected department, and determine the user's authority department according to the user's identity information;

[0090] The number of cases of multidrug-resistant bacteria detected in hospitalized patients during the same period refers to the number of cases of multidrug-resistant bacteria detected in hospitalized patients during the specified time period.

[0091] The multi-drug-resistant bacteria that lead to nosocomial infection should meet the following requirements: the patients were hospitalized at the same time, that is, the statistical time of the patients’ ...

Embodiment 2

[0305] This embodiment proposes a system based on MapReduce and big data management to detect the number of multidrug-resistant bacterial infections in the same period, including:

[0306] The acquisition module is used to acquire hospitalization process information A, department transfer information B, bacterial culture information J, drug susceptibility test information K, selected statistical time, and selected departments, and determine the user's authority department according to the user's identity information;

[0307] The first filtering module is used to divide the transfer information B into transfer information B(a)_Y whose time intersects with the statistical time and transfer information B(a) whose time does not intersect with the statistical time _N;

[0308] The second filtering module is used to divide the transfer information B(a)_Y based on the authority department into the department transfer information B(b)_Y that the department belongs to the authority de...

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Abstract

The invention provides a method and system for synchronously detecting the number of cases infected with multi-drug-resistant bacteria based on MapReduce and big data management. Based on the MapReduce framework, the parallel computing capability of a machine in a distributed system is utilized, the task of calculating the number of cases infected with multi-drug-resistant bacteria in a hospital in millions and tens of millions of inpatients beyond the memory and storage limit of a server is divided into tens of millions and billions of small tasks, the small tasks are simultaneously executedon a plurality of machines, and intermediate output results of the small tasks are summarized to generate a final result. According to the invention, massive parallel computing can be carried out on big data of millions, tens of millions and hundred millions of inpatients according to various calibers such as provincial and municipal areas, hospital levels, hospital beds, comprehensive and specialized departments, publicity and camp, all types of infections related to the multi-drug-resistant bacteria are managed, accurate statistics of the number of cases infected with the multi-drug-resistant bacteria in the hospital is achieved, hospital infection is integrally evaluated, and overall prevention, control and management of hospital infection of the multi-drug-resistant bacteria are achieved.

Description

technical field [0001] The invention belongs to the technical field of managing multi-drug-resistant bacterial infections, and specifically relates to a method and system for detecting the number of multi-drug-resistant bacterial infections in the same period based on MapReduce and big data management, and is especially suitable for the large amount of patient data to be processed. It is far more than a scenario where the storage (disk) and computing power (memory, CPU) of a server cannot be split and assigned tasks manually. Background technique [0002] Multidrug-resistant bacteria refer to pathogenic bacteria with multiple drug resistance. Specifically, it means that a microorganism is resistant to three or more types of antibiotics at the same time, rather than three types of the same type. [0003] Multidrug-resistant bacteria include nine species, namely methicillin-resistant Staphylococcus aureus, vancomycin-resistant Enterococcus faecalis, vancomycin-resistant Enter...

Claims

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Application Information

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IPC IPC(8): G16H10/60G16H50/80G16H70/40
CPCG16H10/60G16H50/80G16H70/40
Inventor 霍瑞林建陈春平
Owner 杭州杏林信息科技有限公司
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