Systematic assessment of data quality and quality assurance/quality control (QA/QC) of current research on microplastics in biosolids and agricultural soils

2022 ◽  
Vol 294 ◽  
pp. 118629
Author(s):  
Shima Ziajahromi ◽  
Frederic D.L. Leusch
PEDIATRICS ◽  
1992 ◽  
Vol 90 (6) ◽  
pp. 959-965
Author(s):  
Terri A. Slagle ◽  
Jeffrey B. Gould

The purpose of this national survey was to define the extent and features of database use by 445 tertiary level neonatal intensive care nurseries in the United States. Of the 305 centers responding to our survey, 78% had a database in use in 1989 and 15% planned to develop one in the future. Nurseries varied remarkably in the volume of data collected, the amount of time devoted to completing data collection forms, and the personnel involved in data collection. Although data were used primarily for statistical reports (93% of nurseries), quality assurance (73%) and research activities (61%) were also enhanced by database information. Neonatal databases were used to generate reports for the permanent medical record in 38% of centers. Satisfaction with the database was dependent on how useful the database information was to centers which collected and actually used a large volume of information. Overall, nurseries expressed a high degree of confidence in the data they collected, and 65% felt their neonatal database information could be used directly in publication of research. It was disturbing that accuracy of data was not monitored formally by the majority of nurseries. Only 27% of centers followed a routine schedule of data quality assurance, and only 53% had built in error messages for data entry. We caution all who receive database information in the form of morbidity and mortality statistics, clinical reports on patients cared for in neonatal units, and published manuscripts to be attentive to the quality of the data they consume. We feel that future database design efforts need to better address data quality control. Our findings stress the importance and need for immediate efforts to better address database quality control.


2010 ◽  
Vol 27 (10) ◽  
pp. 1565-1582 ◽  
Author(s):  
Christopher A. Fiebrich ◽  
Cynthia R. Morgan ◽  
Alexandria G. McCombs ◽  
Peter K. Hall ◽  
Renee A. McPherson

Abstract Mesoscale meteorological data present their own challenges and advantages during the quality assurance (QA) process because of their variability in both space and time. To ensure data quality, it is important to perform quality control at many different stages (e.g., sensor calibrations, automated tests, and manual assessment). As part of an ongoing refinement of quality assurance procedures, meteorologists with the Oklahoma Mesonet continually review advancements and techniques employed by other networks. This article’s aim is to share those reviews and resources with scientists beginning or enhancing their own QA program. General QA considerations, general automated tests, and variable-specific tests and methods are discussed.


2020 ◽  
pp. e2020063
Author(s):  
Soo Min Kim ◽  
Yunsu Choi ◽  
Bo Youl Choi ◽  
Minjeong Kim ◽  
Sang Il Kim ◽  
...  

Author(s):  
Dilumie Abeysirigunawardena ◽  
Marlene Jeffries ◽  
Michael G. Morley ◽  
Alice O.V. Bui ◽  
Maia Hoeberechts

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