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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Green PubHlthRsPract2018 28-3.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:Codesign of the Population Health Information Management System to measure reach and practice change of childhood obesity programs|Codesign of the Population Health Information Management System to measure reach and practice change of childhood obesity programs]]"'''
'''"[[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]]"'''


Childhood obesity prevalence is an issue of international public health concern, and governments have a significant role to play in its reduction. The Healthy Children Initiative (HCI) has been delivered in New South Wales (NSW), Australia, since 2011 to support implementation of childhood obesity prevention programs at scale. Consequently, a system to support local implementation and data collection, analysis, and reporting at local and state levels was necessary. The Population Health Information Management System (PHIMS) was developed to meet this need.
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.


A collaborative and iterative process was applied to the design and development of the system. The process comprised identifying technical requirements, building system infrastructure, delivering training, deploying the system, and implementing quality measures. ('''[[Journal:Codesign of the Population Health Information Management System to measure reach and practice change of childhood obesity programs|Full article...]]''')<br />
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 />
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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...)

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CyberMaster: An expert system to guide the development of cybersecurity curricula
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