Difference between revisions of "Template:Article of the week"

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(Updated article of the week text)
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig0 Cardenia JofFoodDrugAnal2018 26-4.jpg|240px]]</div>
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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Galliano JofPathInfo2019 10.jpg|240px]]</div>
'''"[[Journal:Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L|Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L]]"'''
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'''"[[Journal:Process variation detection using missing data in a multihospital community practice anatomic pathology laboratory|Process variation detection using missing data in a multihospital community practice anatomic pathology laboratory]]"'''
  
A routine method for determining [[wikipedia:Cannabinoid|cannabinoids]] in ''Cannabis sativa'' L. [[wikipedia:Inflorescence|inflorescence]], based on fast [[gas chromatography]] coupled to [[mass spectrometry]] (fast GC-MS), was developed and validated. To avoid the [[wikipedia:Decarboxylation|decarboxylation]] of the carboxyl group of cannabinoids, different derivatization approaches—i.e., silylation and esterification (diazomethane-mediated) reagents and solvents (pyridine or ethyl acetate)—were tested. The methylation significantly increased the signal-to-noise ratio of all carboxylic cannabinoids, except for cannabigerolic acid (CBGA). Since [[wikipedia:Diazomethane|diazomethane]] is not commercially available, is considered a hazardous reactive, and requires one-day synthesis by specialized chemical staff, the process of silylation was used along the entire validation of a routine method. The method gave a fast (total analysis time < 7.0 min) and satisfactory resolution (R > 1.1), with a good repeatability (intraday < 8.38%; interday < 11.10%) and sensitivity (LOD < 11.20 ng/mL). ('''[[Journal:Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L|Full article...]]''')<br />
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[[Barcode]]-driven [[workflow]]s reduce patient identification errors. Missing process timestamp data frequently confound our health system's pending lists and appear as actions left undone. Anecdotally, it was noted that missing data could be found when there is procedure noncompliance. This project was developed to determine if missing timestamp data in the histology barcode-driven workflow correlated with other process variations, procedure noncompliance, or is an indicator of workflows needing focus for improvement projects. Data extracts of timestamp data from January 1, 2018 to December 15, 2018 for the major histology process steps were analyzed for missing data. Case-level analysis to determine the presence or absence of expected barcoding events was performed on 1031 surgical pathology cases to determine the cause of the missing data and determine if additional data variations or procedure noncompliance events were present. The data variations were classified according to a scheme defined in the study. ('''[[Journal:Process variation detection using missing data in a multihospital community practice anatomic pathology laboratory|Full article...]]''')<br />
 
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''Recently featured'':
 
''Recently featured'':
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: ▪ [[Journal:Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L|Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L]]
 
: ▪ [[Journal:Design and refinement of a data quality assessment workflow for a large pediatric research network|Design and refinement of a data quality assessment workflow for a large pediatric research network]]
 
: ▪ [[Journal:Design and refinement of a data quality assessment workflow for a large pediatric research network|Design and refinement of a data quality assessment workflow for a large pediatric research network]]
 
: ▪ [[Journal:Identification of Cannabis sativa L. (hemp) retailers by means of multivariate analysis of cannabinoids|Identification of Cannabis sativa L. (hemp) retailers by means of multivariate analysis of cannabinoids]]
 
: ▪ [[Journal:Identification of Cannabis sativa L. (hemp) retailers by means of multivariate analysis of cannabinoids|Identification of Cannabis sativa L. (hemp) retailers by means of multivariate analysis of cannabinoids]]
: ▪ [[Journal:Data sharing at scale: A heuristic for affirming data cultures|Data sharing at scale: A heuristic for affirming data cultures]]
 

Revision as of 17:35, 16 December 2019

Fig3 Galliano JofPathInfo2019 10.jpg

"Process variation detection using missing data in a multihospital community practice anatomic pathology laboratory"

Barcode-driven workflows reduce patient identification errors. Missing process timestamp data frequently confound our health system's pending lists and appear as actions left undone. Anecdotally, it was noted that missing data could be found when there is procedure noncompliance. This project was developed to determine if missing timestamp data in the histology barcode-driven workflow correlated with other process variations, procedure noncompliance, or is an indicator of workflows needing focus for improvement projects. Data extracts of timestamp data from January 1, 2018 to December 15, 2018 for the major histology process steps were analyzed for missing data. Case-level analysis to determine the presence or absence of expected barcoding events was performed on 1031 surgical pathology cases to determine the cause of the missing data and determine if additional data variations or procedure noncompliance events were present. The data variations were classified according to a scheme defined in the study. (Full article...)

Recently featured:

Development and validation of a fast gas chromatography–mass spectrometry method for the determination of cannabinoids in Cannabis sativa L
Design and refinement of a data quality assessment workflow for a large pediatric research network
Identification of Cannabis sativa L. (hemp) retailers by means of multivariate analysis of cannabinoids