Temporary COVID-19 IT Solutions Provide Permanent Options for Federal Agencies

The pandemic led some agencies to make wholesale changes, such as permanently expanding telework or artificial intelligence initiatives, while others are leaving more subtle remnants of the pandemic.

For instance, while the U.S. Supreme Court switched back from teleconference to in-person hearings in October, it began providing a live audio feed of oral arguments.

“I think both leaders and supervisors found themselves in a position where they had to say yes to a lot of innovations that they previously might have said, ‘Let’s look at that over the next several years,’” says Loren DeJonge Schulman, vice president of research and evaluation at the Partnership for Public Service. “And not only did nothing bad happen, it was wildly successful.”

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Energy Department Lab Fosters Collaboration

What’s extraordinary about the NVBL, explains Buchanan, is that it has “one front door,” meaning all 17 national laboratories worked together. There was an executive committee that met each day and had regular check-ins with the five project leads, who also met daily with their teams. To do that, the labs leaned heavily on collaboration tools such as videoconferencing, chat and file sharing applications.

“National laboratories always had been hotbeds of collaboration. That’s just part of our DNA,” says Buchanan, who was the deputy director for science and technology at Oak Ridge National Laboratory in Tennessee but is on assignment to the Department of Energy Office of Science as a senior technical adviser to the deputy director for ­science programs.

“But it’s different when you’re working on a telephone or you’re working on email versus having somebody’s face in front of you and brainstorming together in real time,” she says.

Because different organizations were involved in the NVBL, they didn’t choose a single platform for the initiative. “We gave the project leads a lot of latitude as to how they managed it,” says Buchanan.

“Ten years ago, I’m not sure you could have pulled this off,” she adds. “I don’t think, frankly, the whole country would have gotten through this mess without these ­web-based communication tools.”

After asking other agencies, universities and industry leaders about the sources of their biggest bottlenecks, the labs focused their energies on five missions: finding potential treatments for the virus; addressing medical supply shortages; developing and verifying COVID-19 testing ­methods; predicting the disease’s spread; and studying how the virus moves through buildings and the environment.

After the initiative is complete, the laboratories can apply the computational tools used during the pandemic for other purposes, Buchanan says.

“We’re for predicting events, like understanding where cars are going to go if there’s an evacuation for a hurricane,” she says. “Some of those tools that we used for COVID will continue being developed as our core missions are concerned.”

There’s language in the 2022 budget that would continue some of the NVBL’s work through the Biopreparedness Research Virtual Environment initiative.

“People feel like there’s more work to do,” Buchanan explains. “Keeping these capabilities together so they don’t go dormant — we don’t have to pull them up from nothing — would be extremely valuable for the country to be prepared for the next round of this or future problems like this.”

EXPLORE: How does culture need to shift to support hybrid work in the federal government?

NIH Forges Collaborative Effort to Combat COVID-19

Like DOE, the National Institutes of Health pulled together a coalition to respond to the COVID-19 crisis, but the idea had been brewing well before the virus emerged.

NIH’s National Institute of Biomedical Imaging and Bioengineering had brought together leaders from different medical imaging associations to discuss the need for a high-quality source of imaging data to expedite machine learning and artificial intelligence for medical imaging.

They were looking for a use case to pilot the idea. “Then COVID hit,” recalls Maryellen Giger, the A.N. Pritzker distinguished service professor of radiology, the Committee on Medical Physics and the College at the University of Chicago.

The idea of a joint ­initiative came to fruition when the Medical Imaging and Data Resource Center was funded in August 2020 to collect, analyze and ­disseminate medical images related to COVID-19. 

MIDRC, which by October had 100 researchers from 24 institutions, is hosted at the University of Chicago and co-led by the Radiological Society of North America, the American College of Radiology and the American Association of Physicists in Medicine.

The center’s first goal is to build the infrastructure around data commons. A major challenge is getting institutions to provide medical images. The ­diversity of data depends on which institutions donate them. MIDRC, through RSNA and ACR, is helping organizations cover the costs of an IT employee to upload images.

MIDRC’s second goal is to use machine learning to research COVID-19. For instance, an algorithm could be used to explore whether it’s possible to assess the severity of a patient’s disease based on image analysis. Ideally, the infrastructure and model for MIDRC will also be used for other illnesses.

One of the unique aspects of MIDRC is its creation of two commons: an open commons and a sequestered ­commons. The sequestered commons will not be accessible, but they will be maintained to test artificial intelligence and machine learning algorithms ­independently to preserve the integrity of the test set and potentially to expedite the regulatory process and translation to the public good.

“We don’t know of any open ­commons like MIDRC, one that aims to yield diverse and trustworthy data that will allow investigators to ask various c­linical questions,” says Giger. “You’re not pigeonholed into one clinical question. Ultimately, we want to be almost disease-agnostic in our collection.”