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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Johannes Cordua Arzt in seinem Studierzimmer.jpg|160px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
A '''[[physician office laboratory]]''' ('''POL''') is a physician-, partnership-, or group-maintained [[laboratory]] that performs diagnostic tests or examines specimens in order to diagnose, prevent, and/or treat a disease or impairment in a patient as part of the physician practice. The POL shows up in primary care physician offices as well as the offices of specialists like urologists, hematologists, gynecologists, and endocrinologists. In many countries like the United States, the physician office laboratory is considered a [[clinical laboratory]] and is thus regulated by federal, state, and/or local laws affecting such laboratories.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


The workflow of a POL is similar to other clinical labs; the difference in workflows mostly comes down to the time spent in transporting the specimen to an outside lab and waiting for the processing. The in-office lab saves time in those parts of the process. Potential benefits of a POL include quicker access to test results for the clinician, greater efficiency of the clinical workflow, cheaper testing, and greater patient comfort and happiness. Potential disadvantages include the physician office being the only point-of-access, patients not feeling comfortable about the physician's office being the central repository of information, and the cost of meeting compliance requirements for local, state, and federal regulations. ('''[[Physician office laboratory|Full article...]]''')<br />
[[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 />
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''Recently featured'': [[United States Department of Health and Human Services]], [[Bioimage informatics]], [[Biobank]]
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Latest 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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