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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Doctor's Office in New Orleans.jpg|120px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
A '''[[rural health clinic]]''' ('''RHC''') is a special facility designation of the U.S. [[Centers for Medicare and Medicaid Services]] (CMS), defined as a clinic in a non-urbanized area designated by the Health Resources and Services Administration as being in a health professional shortage or medically underserved area.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


In September 1999, nearly 3,500 RHCs were operating across 45 states. By January 2013, that number rose to nearly 3,800. RHCs were established by the Rural Health Clinic Services Act of 1977, otherwise known as Public Law 95-210. The program was established to address an inadequate supply of physicians serving Medicare beneficiaries and Medicaid recipients in rural areas and to increase the utilization of non-physician practitioners. To qualify as an RHC the facility must be located in a non-urban area, as described by the United States Census Bureau, and must be defined as being in a medically underserved area by one of several possibilities. ('''[[Rural health clinic|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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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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