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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Crisan PeerJ2018 6.jpg|240px]]</div>
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'''"[[Journal:Evidence-based design and evaluation of a whole genome sequencing clinical report for the reference microbiology laboratory|Evidence-based design and evaluation of a whole genome sequencing clinical report for the reference microbiology laboratory]]"'''
'''"[[Journal:Data to diagnosis in global health: A 3P approach|Data to diagnosis in global health: A 3P approach]]"'''


Microbial genome [[sequencing]] is now being routinely used in many [[Clinical laboratory|clinical]] and [[Public health laboratory|public health laboratories]]. Understanding how to [[Reporting|report]] complex genomic test results to stakeholders who may have varying familiarity with genomics — including clinicians, laboratorians, epidemiologists, and researchers — is critical to the successful and sustainable implementation of this new technology; however, there are no evidence-based guidelines for designing such a report in the pathogen genomics domain. Here, we describe an iterative, human-centered approach to creating a report template for communicating tuberculosis (TB) genomic test results. ('''[[Journal:Evidence-based design and evaluation of a whole genome sequencing clinical report for the reference microbiology laboratory|Full article...]]''')<br />
With connected medical devices fast becoming ubiquitous in healthcare monitoring, there is a deluge of data coming from multiple body-attached sensors. Transforming this flood of data into effective and efficient diagnosis is a major challenge. To address this challenge, we present a "3P" approach: personalized patient monitoring, precision diagnostics, and preventive criticality alerts. In a collaborative work with doctors, we present the design, development, and testing of a healthcare data analytics and communication framework that we call RASPRO (Rapid Active Summarization for effective PROgnosis). The heart of RASPRO is "physician assist filters" (PAF) that 1. transform unwieldy multi-sensor time series data into summarized patient/disease-specific trends in steps of progressive precision as demanded by the doctor for a patient’s personalized condition, and 2. help in identifying and subsequently predictively alerting the onset of critical conditions. ('''[[Journal:Data to diagnosis in global health: A 3P approach|Full article...]]''')<br />
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Revision as of 15:25, 18 March 2019

Fig9 Pathinarupothi BMCMedInfoDecMak2018 18.png

"Data to diagnosis in global health: A 3P approach"

With connected medical devices fast becoming ubiquitous in healthcare monitoring, there is a deluge of data coming from multiple body-attached sensors. Transforming this flood of data into effective and efficient diagnosis is a major challenge. To address this challenge, we present a "3P" approach: personalized patient monitoring, precision diagnostics, and preventive criticality alerts. In a collaborative work with doctors, we present the design, development, and testing of a healthcare data analytics and communication framework that we call RASPRO (Rapid Active Summarization for effective PROgnosis). The heart of RASPRO is "physician assist filters" (PAF) that 1. transform unwieldy multi-sensor time series data into summarized patient/disease-specific trends in steps of progressive precision as demanded by the doctor for a patient’s personalized condition, and 2. help in identifying and subsequently predictively alerting the onset of critical conditions. (Full article...)

Recently featured:

Building a newborn screening information management system from theory to practice
Adapting data management education to support clinical research projects in an academic medical center
Development of an electronic information system for the management of laboratory data of tuberculosis and atypical mycobacteria at the Pasteur Institute in Côte d’Ivoire