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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:HL7 Reference Information Model.jpg|260px]]</div>
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'''[[Health Level Seven]]''' ('''HL7''') is an international non-profit volunteer-based organization involved with the development of international health care informatics interoperability standards. The HL7 community consists of health care experts and information scientists collaborating to create standards for the exchange, management, and integration of electronic health care information. The term "HL7" is also used to refer to some of the specific standards created by the organization (e.g., HL7 v2.x, v3.0, HL7 RIM). HL7 and its members provide a framework (and related standards) for the exchange, integration, sharing, and retrieval of electronic health information. v2.x of the standards, which support clinical practice and the management, delivery, and evaluation of health services, are the most commonly used in the world.
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


In total HL7 develops conceptual standards (e.g., HL7 RIM), document standards (e.g., HL7 CDA), application standards (e.g., HL7 CCOW), and messaging standards (e.g., HL7 v2.x and v3.0). The HL7 messaging standards v2.x and 3.0 are the primary standards from the organization. They provide a framework for data exchange among clinical and healthcare systems in an ideal format. The 2.x standards are flexible, with several implementation options, loosely geared towards "clinical interface specialists" working to move clinical data in the application space. The 3.0 standards are designed to be more fixed, precise, and international, geared towards governments and end users of clinical applications. ('''[[Health Level Seven|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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