Goal 4: Develop Workforce and Resources

Credible Data and Analysis of the Biomedical Research Workforce

There is a need for sensible policies that require collection and scientific analysis of credible data relating to the biomedical workforce. The data currently available are weak – for example no one knows, to a factor of 2X, the actual number of postdocs in the United States. The absence of credible human resource and labor market data on the biomedical research workforce is very surprising. NIH could contribute greatly ...more »

Submitted by (@teitelbaum)

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Goal 2: Reduce Human Disease

Harnessing the Tsunami of Patient-Generated Health Data

How can the NHLBI foster the development of effective tools and methodologies to harness the tsunami of patient-generated health data into a valuable resource for conducting patient-centered research? Some challenges to overcome might include a) how to enable the collaboration of the more traditional clinical scientists with scientists from other disciplines such as informatics or computational and data-enabled science ...more »

Submitted by (@nhlbiforumadministrator)

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10 up votes
11 down votes
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Goal 3: Advance Translational Research

Create a National Action Plan for COPD

Lead a coordinated effort of government, patient advocacy organizations, professional organizations, payers and others to plan and implement a coordinated plan to improve COPD awareness, education for patients and healthcare professionals, treatment strategies, research and data collection, policies and public health infrastructure and programs.

Submitted by (@jsullivan)

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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 »

Submitted by (@nhlbiforumadministrator1)

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4 net votes
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Goal 3: Advance Translational Research

Maximizing Previous Investment in Existing Cohorts

Everyone would like to see integration of genomic, metabolomic, epigenomic, proteomic, transcriptomic, etc. data analyzed in the context of clinical disease, environmental influences, and even end-organ effects (lung versus heart or blood as an example). Rarely can this occur on small cohorts, but rarely are funds available to take maximum use of existing large cohorts and the samples and information collected within ...more »

Submitted by (@nhlbiforumadministrator)

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22 net votes
34 up votes
12 down votes
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Goal 2: Reduce Human Disease

Data from regulatory studies a barrier to evidence-based medicine

Alignment of regulatory, healthcare, and research arms of the government is poor. There is a need to improve the design, quality and usefulness of data from regulatory studies to address major clinical questions and also to facilitate scientific inquiry. This is a barrier to evidence based medicine and improved treatments.

Submitted by (@societyforvascularsurgery)

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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?

Submitted by (@nhlbiforumadministrator)

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13 up votes
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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 »

Submitted by (@greg.martin)

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