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

From LIMSWiki
Jump to navigationJump to search
(Updated article of the week text.)
(Updated article of the week text)
(44 intermediate revisions by the same user not shown)
Line 1: Line 1:
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Bardyn JofESciLib2018 7-2.jpg|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Wang BMCMedInfoDecMak2019 19-1.png|240px]]</div>
'''"[[Journal:Health sciences libraries advancing collaborative clinical research data management in universities|Health sciences libraries advancing collaborative clinical research data management in universities]]"'''
'''"[[Journal:Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory|Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory]]"'''


Medical libraries need to actively review their service models and explore partnerships with other campus entities to provide better-coordinated clinical research management services to faculty and researchers. TRAIL (Translational Research and Information Lab), a five-partner initiative at the University of Washington (UW), explores how best to leverage existing expertise and space to deliver clinical research [[Information management|data management]] (CRDM) services and emerging technology support to clinical researchers at UW and collaborating institutions in the Pacific Northwest. The initiative offers 14 services and a technology-enhanced innovation lab located in the Health Sciences Library (HSL) to support the University of Washington clinical and research enterprise. Sharing of staff and resources merges library and non-library workflows, better coordinating data and innovation services to clinical researchers. Librarians have adopted new roles in CRDM, such as providing user support and training for UW’s Research Electronic Data Capture (REDCap) instance. ('''[[Journal:Health sciences libraries advancing collaborative clinical research data management in universities|Full article...]]''')<br />
n autoverification system for coagulation consists of a series of rules that allows normal data to be released without manual verification. With new advances in [[medical informatics]], the [[laboratory information system]] (LIS) has growing potential for the use of autoverification, allowing rapid and accurate verification of [[clinical laboratory]] tests. The purpose of the study is to develop and evaluate a LIS-based autoverification system for validation and efficiency.
 
Autoverification decision rules—including quality control, analytical error flag, critical value, limited range check, delta check, and logical check rules, as well as patient’s historical information—were integrated into the LIS. Autoverification limit ranges was constructed based on 5% and 95% percentiles. The four most commonly used coagulation assays—prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen (FBG)—were followed by the autoverification protocols. ('''[[Journal:Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory|Full article...]]''')<br />
<br />
<br />
''Recently featured'':
''Recently featured'':
: ▪ [[Journal:Privacy preservation techniques in big data analytics: A survey|Privacy preservation techniques in big data analytics: A survey]]
: ▪ [[Journal:CyberMaster: An expert system to guide the development of cybersecurity curricula|CyberMaster: An expert system to guide the development of cybersecurity curricula]]
: ▪ [[Journal:The development and application of bioinformatics core competencies to improve bioinformatics training and education|The development and application of bioinformatics core competencies to improve bioinformatics training and education]]
: ▪ [[Journal:Costs of mandatory cannabis testing in California|Costs of mandatory cannabis testing in California]]
: ▪ [[Journal:Approaches to medical decision-making based on big clinical data|Approaches to medical decision-making based on big clinical data]]
: ▪ [[Journal:An integrated data analytics platform|An integrated data analytics platform]]

Revision as of 15:52, 11 November 2019

Fig1 Wang BMCMedInfoDecMak2019 19-1.png

"Design and evaluation of a LIS-based autoverification system for coagulation assays in a core clinical laboratory"

n autoverification system for coagulation consists of a series of rules that allows normal data to be released without manual verification. With new advances in medical informatics, the laboratory information system (LIS) has growing potential for the use of autoverification, allowing rapid and accurate verification of clinical laboratory tests. The purpose of the study is to develop and evaluate a LIS-based autoverification system for validation and efficiency.

Autoverification decision rules—including quality control, analytical error flag, critical value, limited range check, delta check, and logical check rules, as well as patient’s historical information—were integrated into the LIS. Autoverification limit ranges was constructed based on 5% and 95% percentiles. The four most commonly used coagulation assays—prothrombin time (PT), activated partial thromboplastin time (APTT), thrombin time (TT), and fibrinogen (FBG)—were followed by the autoverification protocols. (Full article...)

Recently featured:

CyberMaster: An expert system to guide the development of cybersecurity curricula
Costs of mandatory cannabis testing in California
An integrated data analytics platform