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

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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Mrazek Diagnostics21 11-7.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig3 Arifin JofMedBio21 40.png|240px]]</div>
'''"[[Journal:Laboratory demand management strategies: An overview|Laboratory demand management strategies: An overview]]"'''
'''"[[Journal:Error evaluation in the laboratory testing process and laboratory information systems|Error evaluation in the laboratory testing process and laboratory information systems]]"'''


Inappropriate [[laboratory]] test selection in the form of overutilization as well as underutilization, frequently occurs despite available guidelines. There is broad approval among laboratory specialists and clinicians that [[demand management]] (DM) strategies are useful tools to avoid this issue. Most of these tools are based on automated algorithms or other types of [[machine learning]]. This review summarizes the available DM strategies that may be adopted to local settings. We believe that [[artificial intelligence]] (AI) may help to further improve these available tools. ('''[[Journal:Laboratory demand management strategies: An overview|Full article...]]''')<br />
The [[laboratory]] testing process consists of five analysis phases, featuring the total testing process (TTP) framework. Activities in laboratory processing, including those of testing, are error-prone and affect the use of [[laboratory information system]]s (LIS). This study seeks to identify error factors related to system use, as well as the first and last phases of the laboratory testing process, using a proposed framework known as the "total testing process for laboratory information systems" (TTP-LIS). We conducted a qualitative case study evaluation in two private [[hospital]]s and a [[Clinical laboratory|medical laboratory]]. We collected data using interviews, observations, and document analysis methods involving physicians, nurses, an information technology officer, and the laboratory staff... ('''[[Journal:Error evaluation in the laboratory testing process and laboratory information systems|Full article...]]''')<br />
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''Recently featured'':
''Recently featured'':
{{flowlist |
{{flowlist |
* [[Journal:Laboratory demand management strategies: An overview|Laboratory demand management strategies: An overview]]
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* [[Journal:A scoping review of integrated blockchain-cloud architecture for healthcare: Applications, challenges, and solutions|A scoping review of integrated blockchain-cloud architecture for healthcare: Applications, challenges, and solutions]]
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* [[Journal:Laboratory information management system for the biosafety laboratory: Safety and efficiency|Laboratory information management system for the biosafety laboratory: Safety and efficiency]]
* [[Journal:Use of middleware data to dissect and optimize hematology autoverification|Use of middleware data to dissect and optimize hematology autoverification]]
}}
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Revision as of 16:05, 11 July 2022

Fig3 Arifin JofMedBio21 40.png

"Error evaluation in the laboratory testing process and laboratory information systems"

The laboratory testing process consists of five analysis phases, featuring the total testing process (TTP) framework. Activities in laboratory processing, including those of testing, are error-prone and affect the use of laboratory information systems (LIS). This study seeks to identify error factors related to system use, as well as the first and last phases of the laboratory testing process, using a proposed framework known as the "total testing process for laboratory information systems" (TTP-LIS). We conducted a qualitative case study evaluation in two private hospitals and a medical laboratory. We collected data using interviews, observations, and document analysis methods involving physicians, nurses, an information technology officer, and the laboratory staff... (Full article...)

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