CDC data modernization lead outlines 4 challenges to tracking COVID-19


The Centers for Disease Control and Prevention’s acting deputy director for public health science and surveillance on Monday said the U.S. is handicapped when collecting COVID-19 data and tracking the outbreak.

Here are the four challenges Dr. Dan Jernigan shared during a panel discussion at HHS’ Office of the National Coordinator for Health Information Technology’s virtual annual meeting:

  1. 1. There’s no standard, scalable process for reporting cases of novel diseases, Jernigan said. While case-based surveillance does exist for certain diseases, such as for HIV, malaria and smallpox, there wasn’t a quick, standard system to track an emerging outbreak. “There’s not a generic case-based surveillance system,” Jernigan said. “Looking forward, that’s a challenge we’re going to have to address.”

Jernigan leads the CDC’s Data Modernization Initiative and also co-chairs a work group with ONC chief Micky Tripathi to review public health data systems and their ability to detect and respond to COVID-19 and future public health threats, as required under an executive order that President Joe Biden signed in January.

2. Jernigan called on the need to ease sharing of data between different types of sources. Much of the emphasis on interoperability to date has focused on linking up electronic health record systems with one another, but for effectively tracking a disease outbreak, it’s also important to tie in providers like laboratories that are testing patients for a disease.

Dr. Norman Oliver, state health commissioner at the Virginia Department of Health and another participant on the panel, said commercial labs sent dozens of COVID-19 test results in ways that weren’t compatible with the department’s software system. Even though the data was sent electronically, it was almost as bad as using paper records, he said.

They “weren’t coming in on fax machines, but they might as well have been,” Oliver said. “We were manually pushing that data” into the department’s software system.

Tripathi, who moderated the panel, suggested that to effectively modernize IT infrastructure, the healthcare industry should stop thinking of public health data systems as distinct and separate from clinical and laboratory systems, and instead consider public health as part of a data-sharing ecosystem that includes all of the healthcare sectors.

“We need to really be thinking about a public health ecosystem,” Tripathi said.

3. On a similar note, Jernigan said COVID-19 interventions and vaccinations have taken place in various care settings, including patient homes, pharmacies and alternate care sites. He said public health agencies have to ensure they’re connected to those “non-traditional” care sites, which are often caring for disadvantaged populations that might be missed if only relying on data from traditional healthcare encounters.

4. Jernigan said states vary in how and whether they capture race and ethnicity data, which has made it challenging to assess COVID-19 response alongside health equity concerns.

Setting standard approaches for what data is collected could help fix that problem. So could standardizing how the data’s collected, so it can be shared more easily between organizations.

For example, race and ethnicity data have only been collected in about 60% of vaccinations reported in the U.S. so far, said Dr. Marcella Nunez-Smith, chair of the U.S. COVID-19 Health Equity Task Force and associate dean for health equity research at Yale School of Medicine during the session.

“The early evidence suggests that we are seeing inequities in that vaccination space,” Nunez-Smith said. “But we’re limited by incomplete data.”

Be sure to join us for Modern Healthcare’s Transformation Summit on May 18-19 where Micky Tripathi will present the keynote address on the future of interoperability under the Biden administration. First-time registrants will receive a 15% discount with the code MHOffer. For information, click here.



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