scholarly journals «RISK-PROFILE» OF THE TEST LABORATORY

Author(s):  
V.I. Kravchuk ◽  
◽  
A I. Korobko

Goal of the study is to improve the laboratory management system. The substantiation of principles classification and assessment of risks are carried out. The mind-activity methodology is used. To achieve the goal it is necessary to determine the source of risk, assess a scale of selected risk impact, establish reference (control) points, assess the risk, develop and implement corrective actions. Research methods. The mind-activity methodology is the basic method for research. Application to the risk management process of testing laboratory activities. The results of the study. The levels of the hierarchy are determined by the level of consequences (low, high, medium) from the onset of a negative situation. The phases are determined by the type (category) of risk by the stage of its determination. Forecasted risks are determined by the method of forecasting for a certain future period of time (for example, the next calendar year). In fact, identified are risks that have been identified and are aimed at the short-term perspective of their emergence. Not detected - risks remain identified and arise from the implementation of inappropriate preventive measures. These risks are stipulated by the uncertainty of the input information in the analysis of risks and the inadequacy of measures to eliminate possible negative consequences. The proposed risk classification system makes it possible to compile a “risk profile” of the laboratory. The "Risk-Profile" of a laboratory is a conditional indicator that characterizes the laboratory's ability to possibly provide unreliable test results. Conclusions. The mind-activity methodology was used. Principles, classification and risk assessment method have been developed for the testing laboratory. This made it possible to establish the relationship between the level of risk, its source and the period of exposure, as well as to identify the most vulnerable elements of the management system at a given time and to find ways to improve and search for opportunities. The scientific value of the study lies in the substantiation of the principles classification and method of risk assessment of the testing laboratory. The practical value of the study lies in the possibility of forming a "risk profile" of the laboratory, provides objective information about the current state of the laboratory management system and indicates possible ways of improvement.


2020 ◽  
Vol 34 (5) ◽  
pp. 627-640 ◽  
Author(s):  
Shi Xianwu ◽  
Qiu Jufei ◽  
Chen Bingrui ◽  
Zhang Xiaojie ◽  
Guo Haoshuang ◽  
...  


Author(s):  
Zuzhen Ji ◽  
Dirk Pons ◽  
John Pearse

Successful implementation of Health and Safety (H&S) systems requires an effective mechanism to assess risk. Existing methods focus primarily on measuring the safety aspect; the risk of an accident is determined based on the product of severity of consequence and likelihood of the incident arising. The health component, i.e., chronic harm, is more difficult to assess. Partially, this is due to both consequences and the likelihood of health issues, which may be indeterminate. There is a need to develop a quantitative risk measurement for H&S risk management and with better representation for chronic health issues. The present paper has approached this from a different direction, by adopting a public health perspective of quality of life. We have then changed the risk assessment process to accommodate this. This was then applied to a case study. The case study showed that merely including the chronic harm scales appeared to be sufficient to elicit a more detailed consideration of hazards for chronic harm. This suggests that people are not insensitive to chronic harm hazards, but benefit from having a framework in which to communicate them. A method has been devised to harmonize safety and harm risk assessments. The result was a comprehensive risk assessment method with consideration of safety accidents and chronic health issues. This has the potential to benefit industry by making chronic harm more visible and hence more preventable.



2021 ◽  
Vol 420 ◽  
pp. 129893
Author(s):  
Zijian Liu ◽  
Wende Tian ◽  
Zhe Cui ◽  
Honglong Wei ◽  
Chuankun Li


2021 ◽  
Vol 102 ◽  
pp. 102134
Author(s):  
Junjiang He ◽  
Tao Li ◽  
Beibei Li ◽  
Xiaolong Lan ◽  
Zhiyong Li ◽  
...  


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hamid Reza Marateb ◽  
Maja von Cube ◽  
Ramin Sami ◽  
Shaghayegh Haghjooy Javanmard ◽  
Marjan Mansourian ◽  
...  

Abstract Background Already at hospital admission, clinicians require simple tools to identify hospitalized COVID-19 patients at high risk of mortality. Such tools can significantly improve resource allocation and patient management within hospitals. From the statistical point of view, extended time-to-event models are required to account for competing risks (discharge from hospital) and censoring so that active cases can also contribute to the analysis. Methods We used the hospital-based open Khorshid COVID Cohort (KCC) study with 630 COVID-19 patients from Isfahan, Iran. Competing risk methods are used to develop a death risk chart based on the following variables, which can simply be measured at hospital admission: sex, age, hypertension, oxygen saturation, and Charlson Comorbidity Index. The area under the receiver operator curve was used to assess accuracy concerning discrimination between patients discharged alive and dead. Results Cause-specific hazard regression models show that these baseline variables are associated with both death, and discharge hazards. The risk chart reflects the combined results of the two cause-specific hazard regression models. The proposed risk assessment method had a very good accuracy (AUC = 0.872 [CI 95%: 0.835–0.910]). Conclusions This study aims to improve and validate a personalized mortality risk calculator based on hospitalized COVID-19 patients. The risk assessment of patient mortality provides physicians with additional guidance for making tough decisions.



2021 ◽  
Vol 69 ◽  
pp. 104397
Author(s):  
Lei Pang ◽  
Jiaojiao Cao ◽  
Ran Ma ◽  
Yu Zhao ◽  
Kai Yang


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