Launched in 2016, the Healthy Nevada Project is combining genetic, clinical, environmental and socioeconomic data to better understand the complex interplay between these factors and related effects on population health.
The pilot phase of the Healthy Nevada Project enrolled 10,000 participants in less than 48 hours and then completed subsequent DNA sample collection from each participant in just 60 working days. The second phase of the study will offer open enrollment to an additional 40,000 Nevadans starting in March 2018.
In addition, the Renown Institute for Health Innovation (Renown IHI) also announced it will partner with SAS, an analytics company to gain insights from the health data. Renown IHI is a collaboration between Renown Health, an integrated healthcare network serving Nevada, Lake Tahoe and northeast California, and the Desert Research Institute. Renown IHI research teams are focused on integrating personal healthcare and environmental data with socioeconomic determinants to help Nevada address some of its most complex environmental health problems; while simultaneously expanding the state’s access to leading-edge clinical trials and fostering new connections with biotechnology and pharmaceutical companies.
Researchers, doctors and data scientists from Renown IHI are using SAS to develop a health determinants platform that will surface population health risks from patient variables such as gender, age, and personal or family health history. The platform will also model public health risks ranging from disease and illness to the effects of environmental factors such as air quality, according to a press release.
“SAS is the only vendor in the advanced analytics market with the proven capability and capacity to extract, control and infer numerically validated results from extraordinarily large data sets like those in the health care and environmental science sectors,” Jim Metcalf, chief data scientist of the Healthy Nevada Project, said in a statement.
Insights and understandings gained from SAS Analytics are helping Renown IHI analyze population health outcomes and their correlations to participant genetic information and varying environmental factors such as air and water quality.
“We are working to understand how environmental factors can help predict who may be at risk, allow for quicker diagnoses, and encourage the development of more precise treatments,” Metcalf said. “The modern statistical and machine learning methods, along with the intuitive data visualizations made possible by SAS software, have been critical elements of our success to date.”
Study participants are given no-cost access to genetic testing.
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