Improving Data Intelligence through Data Science and Informatics

The amount of data produced and consumed within the health care sector is growing in volume and complexity. Rapid advances in genomic medicine and evidence-based standards will include data points several orders of magnitude more complex than traditional medical records. New technologies and digital capabilities are enabling real-time data collection from a variety of new sources, such as mobile health applications, sensors, medical devices, and remote patient monitoring tools. These massive quantities of data, known as ‘big data,’ contain insights that could help to improve the quality and cost of health care. But translating all of the data into meaningful intelligence that can improve health outcomes will require new methods for evaluating, managing, and storing data across the continuum – form research laboratories to patient care at bedside.  

The Nell Hodgson Woodruff School of Nursing’s Center for Data Science is dedicated to unlocking the power of big data to improve health outcomes through better clinical decision support, disease surveillance, and population health management.

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The Center for Data Science is developing systems and tools to support collaborative nursing research across academic and practice settings. Through this effort, researchers are working to identify and join datasets in a common data repository that will enable the School of Nursing – and eventually other academic institutions to bring the power of an increased sample size to bear on research questions of interest. The data repository will enable researchers to share and compare nursing research insights and evidence that could be used to prevent, diagnose, treat and evaluate the health of individuals, families, communities and populations.

Initial research focuses include:

  • Cardiovascular
  • Symptom Science/Neurocognition
  • Oncology Patient-Reported Outcomes
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Nursing data elements within the Electronic Medical Record (EMR) have the potential to enhance clinical care and research. Researchers in the Center for Data Science are developing the tools and infrastructure that will enable insights from electronic health records to be efficiently leveraged for use in translational research and establishing a health trajectory across a patient’s life course.

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Emerging technologies such as virtual and augmented reality, mobile and telehealth health applications, sensors, medical devices, and remote patient monitoring tools are  transforming patient care. Researchers at the Center for Data Science are developing new tools to support nursing research, education and practice that will enable better disease prevention, patient self-management, and treatment adherence.

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