Showing 8 ideas for tag "big"
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Goal 4: Develop Workforce and Resources

Quantitative training in the era of big data

Should training in biostatistics, computer science, bioinformatics become broader for the entire biomedical community in this era of very large data sets?

 

How can we grow the number of specialists in biostatistics (and these related fields) without causing an oversupply?

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40 net votes
55 up votes
15 down votes
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Goal 3: Advance Translational Research

Embedding Clinical Trials in Learning Health Systems

What are the best methods for using genotype information and other EMR data to randomize heart, lung, blood, sleep patients to different treatment strategies? One big challenge is how to consent patients for this sort of trial. Must patients be consented separately for every such trial or could there be blanket consent for participating in the learning health care model? This would also require a paradigm shift in how... more »

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4 net votes
15 up votes
11 down votes
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(@greg.martin) kudos icon +

Goal 1: Promote Human Health

Predictive analytics to engage healthy behaviors and maintain health while reducing cost

Predictive Health employs the principle that using modern health testing and predictive analytics will better define true health (not just absence of disease) and, in combination with large-scale data analytics, will facilitate predicting deviations from the healthy trajectory earlier than traditional disease diagnosis, thus allowing more effective and less costly interventions to maintain health. Predictive Health educates... more »

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5 net votes
9 up votes
4 down votes
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Goal 3: Advance Translational Research

Leveraging big data for T4 translation research

What approaches can help leverage the emerging big data in health and health care for observational and interventional implementation research in heart, lung, blood, sleep diseases?

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16 up votes
16 down votes
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(@nhlbiforumadministrator) kudos icon +

Goal 1: Promote Human Health

leveraging EHR through improved partnerships

Large medical delivery systems have an abundance of information stored in their EHR systems. What steps are necessary to develop partnerships between NHLBI and medical delivery systems or other agencies such as AHRQ to access these EHR systems, develop a common terminology (if icd 9 and other common codes are ineffective for merging data) and add that data to dbGap for NIH/community use?

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13 up votes
12 down votes
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