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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig4 Andellini BMCMedInfoDecMak2017 17-1.gif|240px]]</div>
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'''"[[Journal:Experimental application of business process management technology to manage clinical pathways: A pediatric kidney transplantation follow-up case|Experimental application of business process management technology to manage clinical pathways: A pediatric kidney transplantation follow-up case]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


Using a business process management platform, we implemented a specific application to manage the clinical pathway of pediatric patients, and we monitored the activities of the coordinator in charge of case management during a six-month period (from June 2015 to November 2015) using two methodologies: the traditional procedure and the one under study. The application helped physicians and nurses to optimize the amount of time and resources devoted to management purposes. In particular, time reduction was close to 60%. In addition, the reduction of data duplication, the integration of event management, and the efficient collection of data improved the quality of the service. The use of business process management technology, usually related to well-defined processes with high management costs, is an established procedure in multiple environments; its use in healthcare, however, is innovative. ('''[[Journal:Experimental application of business process management technology to manage clinical pathways: A pediatric kidney transplantation follow-up case|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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