Division of Cardiovascular Diseases Strategic Plan

Goals in Enabling Technologies and Methodologies for Cardiovascular Disease

1.2. Develop new bioinformatic tools for cardiovascular medicine

Table of Contents

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Overview

The NHLBI supports outstanding basic, translational, and clinical/epidemiological research and tool/resource development. The impact of these investments could be maximized by developing informatics tools to accelerate knowledge mining and discovery from existing sources. Bio-informatic advances will have to be applied in a manner protective of patient privacy and informed consent. Specific examples may include:

  • Combine EHRs with research databases and biorepositories from epidemiological and clinical studies. These two types of data systems are currently separate and not interoperable.
  • Facilitate collaboration, sharing, and reuse of existing data and tool resources to leverage research investments, elucidate best practices, and accelerate new discovery. Such efforts would make resources, tools, and data more available to researchers and support the development of new hypotheses based on broader and more robust data; foster recognition for researchers who effectively share data and resources with the research community, and identify the most effective approaches to sharing.

Strategies to Accomplish this Goal May Entail:

Basic Research:

  • Improve accessibility and use of proteomic, functional genomic, phenotypic data that are intended for sharing with the research community by providing a searchable, web-accessible database that lists data and resources being made available to the community.

Translational Research:

  • Integrate electronic health records (EHRs) with research databases to support personalized medicine and knowledge mining and to develop and validate tools for clinical decision support. Ethical, legal, and social implications issues should also be incorporated and considered. 
    • Query data from EHR systems for pharmaco-vigilance to allow for studies on the genetics of adverse drug reactions.
    • Use existing data in EHRs to develop tools for risk assessment and for clinical decision-making.
    • Accelerate translation of basic findings to clinical practice by improving the efficiency of data reuse and interpretation within and across disciplines. This goal may be advanced through development of mechanisms to enhance data sharing and pooling across clinical studies. Another example is to identify basic and translational research that supports clinical findings and that can inform study design and rationale
    • Use EHRs and associated databases for molecular research to determine the role of genetics in health and disease. Identify the genetic predictors of specific conditions such as atrial fibrillation, heart failure, and sudden cardiac death, providing direction for prospective confirmatory investigation.
    • Promote the transition from government-supported to self-sustaining informatic infrastructure; facilitate community-based efforts at data sharing and integration.
    • Leverage existing infrastructure and tools arising from the National Centers for Biomedical Computing (NCBC) and Clinical and Translational Science Award (CTSA) programs.

Clinical Research:

  • Incorporate clinical trials or epidemiological data into an EHR system.
    • Research data from a clinical study or database could be combined, added, or put into an EHR system or made interoperable with an existing system to allow for research discovery, replication, and validation studies. Such integration would allow the NHLBI to capitalize on existing resources, combine data across studies/systems, and increase sample sizes and power for clinical studies. It would also facilitate research in a broad population of study subjects.
  • Use EHRs to identify potential patient participants for clinical studies.

Contributing Sources:

September 2008

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