UCI to Lead Transfer of UC COVID-19 Patient Information to Federal Database
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Steve Zylius/UC Irvine
“Rather than going to each of our campuses, we fashioned an agreement where we would share our database,” says Dr. Dan M. Cooper, associate vice chancellor for clinical and translational science at UCI, of integrating University of California patient information into a centralized national platform to help fight COVID-19.
Easily accessible, centralized records will facilitate further research into the disease
Vaccines are here, but as COVID-19 cases continue and variants spread, researchers need easy access to a wide variety of data to better understand the disease. Led by the University of California, Irvine, UC hospitals have received a $500,000 grant from the National Institutes of Health to make this possible.
Dr. Dan M. Cooper, associate vice chancellor for clinical and translational science at UCI, will manage a transfer of UC information on COVID-19 cases into the National COVID Cohort Collaborative’s centralized data resource at the NIH’s National Center for Advancing Translational Sciences.
“We were very involved in the pandemic from Day One,” said Cooper, who’s chair of UC Biomedical Research Acceleration, Integration and Development, a coalition of all five UC health centers – those at UCI, UC San Francisco, UC San Diego, UC Davis and UCLA – with NIH funding for translational research.
In June, the National COVID Cohort Collaborative, known as N3C, launched an analytics platform for electronic health records so that researchers could more easily investigate coronaviruses. Its Data Enclave has collected records from more than 1 million patients.
Researchers pursuing COVID-19-related studies can apply for quick access to detailed case data, including demographics, symptoms, medications, lab test results and outcomes. Though most personal information is not included, patient ZIP codes and dates of service are. Data will continue to feed into the secure system for five years to help address both immediate and long-term questions about the disease.
In a June statement, the NIH said: “Having access to a centralized enclave of this magnitude will help researchers and healthcare providers answer clinically important questions they previously could not, such as ‘Can we predict who might need dialysis because of kidney failure?’ or ‘Who might need to be on a ventilator because of lung failure?’ and ‘Are there different patient responses to coronavirus infection that require distinct therapies?’”
UC health centers have also collected a large amount of data from COVID-19 patients. The $500,000 grant will allow Cooper’s team to incorporate it into the N3C Data Enclave, making case records available on a national scale.
“Rather than going to each of our campuses, we fashioned an agreement where we would share our database,” Cooper said. The UCs will securely contribute such patient information as age, sex, weight, medications and conditions such as high blood pressure or diabetes – with identifying details removed.
“The huge value of this large database is identifying the risk factors,” Cooper said. “There may be medications that are being given out that actually improve the condition.”
Collaborators within the UC Biomedical Research Acceleration, Integration and Development coalition include Dr. Gary Firestein of UC San Diego, Dr. Ted Wun of UC Davis, Dr. Harold Collard of UC San Francisco, Dr. Steve Dubinett of UCLA and UC BRAID Executive Director Laurie Herraiz.
This partnership is part of an effort within UCI to organize health-related data and make it available to researchers across campus. UCI’s Collaboratory of Data in Health and Wellness created a patient database that’s easily accessible to researchers and allows for collaboration among scholars, medical providers and patients to advance healthcare.
“UCI researchers combined the data from the N3C Data Enclave with data in the collaboratory,” said Tom Andriola, vice chancellor for information, technology and data. “This is providing UCI investigators and their collaborators an environment designed for rapid, data-driven discovery.”
