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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab2 Alsaffar JMIRMedicalInfo2017 5-1.png|240px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial|The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''
The way [[electronic health record]] and [[Computerized physician order entry|laboratory test ordering system]] software is designed may influence physicians’ prescription. A randomized controlled trial was performed to measure the impact of a diagnostic and laboratory tests ordering system software modification.


Participants were family physicians working and prescribing diagnostic and [[laboratory]] tests. The intervention group had modified software with basic shortcut menu changes, where some tests were withdrawn or added, and with the implementation of an evidence-based [[clinical decision support system]] based on United States Preventive Services Task Force (USPSTF) recommendations. This intervention group was compared with typically used software (control group).
[[Information]] is the cornerstone of [[research]], from experimental data/[[metadata]] and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging [[laboratory information management system]]s (LIMS) to transform this large information load into useful scientific findings. The development of [[mathematical model]]s that can predict the properties of biological systems is the holy grail of [[computational biology]]. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... ('''[[Journal:Ten simple rules for managing laboratory information|Full article...]]''')<br />


The outcomes were the number of tests prescribed from those: withdrawn from the basic menu; added to the basic menu; marked with green dots (USPSTF’s grade A and B); and marked with red dots (USPSTF’s grade D). ('''[[The effect of a test ordering software intervention on the prescription of unnecessary laboratory tests - A randomized controlled trial|Full article...]]''')<br />
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Revision as of 18:03, 10 June 2024

Fig2 Berezin PLoSCompBio23 19-12.png

"Ten simple rules for managing laboratory information"

Information is the cornerstone of research, from experimental data/metadata and computational processes to complex inventories of reagents and equipment. These 10 simple rules discuss best practices for leveraging laboratory information management systems (LIMS) to transform this large information load into useful scientific findings. The development of mathematical models that can predict the properties of biological systems is the holy grail of computational biology. Such models can be used to test biological hypotheses, guide the development of biomanufactured products, engineer new systems meeting user-defined specifications, and much more ... (Full article...)

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