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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig5 Jang JMIRMedInfo2014 2-2.jpg|220px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig2 Berezin PLoSCompBio23 19-12.png|240px]]</div>
'''"[[Journal:Return on investment in electronic health records in primary care practices: A mixed-methods study|Return on investment in electronic health records in primary care practices: A mixed-methods study]]"'''
'''"[[Journal:Ten simple rules for managing laboratory information|Ten simple rules for managing laboratory information]]"'''


The use of [[electronic health record]]s (EHR) in clinical settings is considered pivotal to a patient-centered health care delivery system. However, uncertainty in cost recovery from EHR investments remains a significant concern in primary care practices.
[[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 />


Guided by the question of “When implemented in primary care practices, what will be the return on investment (ROI) from an EHR implementation?”, the objectives of this study are two-fold: (1) to assess ROI from EHR in primary care practices and (2) to identify principal factors affecting the realization of positive ROI from EHR. We used a break-even point, that is, the time required to achieve cost recovery from an EHR investment, as an ROI indicator of an EHR investment. Given the complexity exhibited by most EHR implementation projects, this study adopted a retrospective mixed-method research approach, particularly a multiphase study design approach. For this study, data were collected from community-based primary care clinics using EHR systems. ('''[[Journal:Return on investment in electronic health records in primary care practices: A mixed-methods study|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...)

Recently featured: