Online Program

Using "Big Data" analytics and health care informatics to advance personalized health

Monday, November 2, 2015

Erin Payne, PhD, MPH, Northrop Grumman Health, McLean, VA
Alex Carlisle, PhD, Health Division, Northrop Grumman, McLean, VA
Sanjiv Desai, MD, Health Division, Northrop Grumman, McLean, VA
Michael Grasso, MD, PhD, FACP, University of Maryland School of Medicine, Baltimore, MD
Background: As “Big Data” becomes more common in clinical settings, there is an increasing need for health care informatics tools and technologies to better manage, process, analyze, and translate this data into actionable results that will advance the practice of personalized healthcare.

Objective/purpose: This presentation will highlight industry-university partnership approaches to challenges associated with big data analytics in the healthcare setting.

Methods: Tools such as cloud data storage and processing, molecular analytics, and natural language processing (NLP) techniques were applied/used to analyze large clinical data sets (up to 40,000 subjects) and identify factors and trends that better define clinical subpopulations and their characteristics.

Results: The use of cloud technologies resulted in a reduction of analysis time from hours down to approximately 13 seconds. NLP tools enabled the presentation of vital text based information in near real-time (less than 5 seconds). Integrated clinical and molecular analytics identified potentially novel biomarkers for risk predictions in cancer patients, and identified the impact of various health and behavioral factors on coronary artery disease (CAD) patients, versus controls.

Discussion/conclusions: Using “Big Data” analytics and health care informatics as in this study can help advance the field of personalized health and provide information to improve health outcomes and reduce healthcare costs. Collectively this should ultimately lead to changes in healthcare policy and enhancements in population health.

Learning Areas:

Basic medical science applied in public health
Clinical medicine applied in public health
Implementation of health education strategies, interventions and programs
Other professions or practice related to public health
Public health or related research

Learning Objectives:
Describe how the combination of structured and unstructured data mining can aid clinicians, leading to new treatments and preventive actions. Explain the benefits of integrated molecular analytics. Discuss how big data and health care informatics can provide evidence to inform health policies. Discuss how the integration of clinical and new data sources not traditionally included in electronic health record structured formats advances health care informatics.

Keyword(s): Information Technology

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am a Scientific Adviser in the Life Sciences program at Northrop Grumman Corporation. I provide subject matter expertise for our personalized healthcare research efforts, and am familiar with our NIH and CDC projects and their relationship with Public Health. I have been a member of APHA for a number of years, and held leadership roles with the Genomics Forum a few years ago.
Any relevant financial relationships? Yes

Name of Organization Clinical/Research Area Type of relationship
Northrop Grumman Personalized Health Employment (includes retainer)

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.