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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Tab2 Matthews JPathInfo2017 8.jpg|240px]]</div>
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'''"[[Journal:Usability evaluation of laboratory information systems|Usability evaluation of laboratory information systems]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Numerous studies have revealed widespread clinician frustration with the usability of [[electronic health record]]s (EHRs) that is counterproductive to adoption of EHR systems to meet the aims of healthcare reform. With poor system usability comes increased risk of negative unintended consequences. Usability issues could lead to user error and workarounds that have the potential to compromise patient safety and negatively impact the quality of care. While there is ample research on EHR usability, there is little [[information]] on the usability of [[laboratory information system]]s (LIS). Yet, an LIS facilitates the timely provision of a great deal of the information needed by physicians to make patient care decisions. Medical and technical advances in genomics that require processing of an increased volume of complex [[laboratory]] data further underscore the importance of developing a user-friendly LIS. This study aims to add to the body of knowledge on LIS usability. ('''[[Journal:Usability evaluation of laboratory information systems|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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