By Margaret Lindquist | June 2021
Early in 2020, medical researchers and clinicians lacked critical information about the COVID-19 pandemic: where the virus was most prevalent, how many people were sick, and where the virus was most likely to erupt next. They needed real-world—and real-time—data.
One result of the pandemic is that the interest in gathering and quickly putting to use real-world health data has accelerated within the healthcare and life sciences communities. For example, the centralized data gathered by the UK’s National Health Service (NHS) has proved to be a treasure trove of insights.
“So much of what we learned, especially in the first year, around therapies and standards of care, came from the UK,” said Dr. David Agus, CEO of the Lawrence J. Ellison Institute for Transformative Medicine, during a recent panel discussion. For example, studies in the UK discovered that the common steroid dexamethasone could reduce mortality by 20%—a huge effect from an inexpensive, widely available drug. “To date, it’s the only drug that is very effective in treating COVID-19,” said fellow panelist Dr Nicholas Christakis, codirector of the Yale Institute for Network Science.
Using data to humanize healthcare was the topic of the May 18, 2021, panel discussion with three healthcare leaders who have worked on COVID-19 in the past year. The event, sponsored by Oracle, brought together Dr. Agus, Dr. Christakis, and Craig Anderson, head of external reporting services at the NHS Business Services Authority.
For Agus, one of the most remarkable advances in the past year has been the continual collection of data around vaccines, even after they’ve been approved for use.
“For the first time in human history, after a drug or vaccine is approved, we continued to collect data,” said Agus. He explained that normally, once a pharmaceutical company has submitted the results of a clinical trial to the appropriate government agency (in the United States, the Federal Drug Administration) they would stop collecting data. But using a tool developed by Oracle for the Centers for Disease Control and Prevention (CDC), data collection around the COVID-19 vaccines continued and has helped determine additional details and depth about the safety and efficacy of the vaccines. The v-safe after vaccination health checker, powered by Oracle Cloud Infrastructure, allowed vaccine recipients to use their mobile devices to let the CDC know about any symptoms in the days, weeks, and months after vaccination. V-safe data has been used to show that it is safe for pregnant women to get the vaccine—safe for the mother and the child. “That's where this pandemic has pushed us—without data, we aren’t coming out of this,” says Agus.
Real-world data is also playing a key role in tracking new variants and determining how those variants are reacting to vaccines, said Christakis. The work that the NHS has done has been a critical part of this effort.
“We’ve never before gotten results this quickly, but that was all because of data collection systems, data analytics systems, and structured data. We’ll go forward now using real-world evidence data.”
“In this we have to rely on the British, who, because of the NHS, are better able to link genetic data about the variants with phenotypic data about what's happening in people,” said Christakis. The NHS was able to sequence the genotypes of many more COVID-19 patients in the UK as the US was able to do in the same amount of time.
Medical researchers have worked for many years toward sharing data better, but it took a global pandemic to clear some obstacles that hindered those efforts. Here are some examples.
Bringing cloud technologies to bear. Anderson believes that the work that has been done over the past year could not have been done even just a few years ago, as the technologies that are now in place have taken clinical research and medical treatment to a new level. That technology includes today’s cloud computing that adds capacity and speed unthinkable in the past. “[At the NHS Business Services Authority] we process something like a hundred million rolls of patient data every month,” said Anderson. “Doing that without technology is next to impossible. Doing things in the cloud means it's more secure.” Agus said that he has seen the benefits of the cloud in real time, working with Oracle and with people all over the world to develop a registration system for vaccines in Africa. “In my business, the cloud has changed everything,” says Agus. With Oracle’s help, he adds, Africa is able to leapfrog vaccine-tracking capabilities in the United States. “They went from paper cards, which we [in the US] still have, to a cloud-based registration system, which has to be the future of what we're doing,” says Agus.
Getting everyone involved. At the beginning of the pandemic, an average of 10 papers a day were published, something that Christakis had no trouble keeping up with. By March, the deluge of content would have been impossible to manage without a huge staff of people filtering information. “Scientists shared preliminary research online and relied on the innovations in data science and in internet infrastructure,” Christakis said. That flow of ideas within the scientific community sped up work scientists and doctors were doing to respond to the pandemic. In turn, Anderson is heartened by the increase in data literacy among the general population over the past 18 months. “I think a lot of the population has spent over a year now looking at new data, understanding what the data means,” he said. “From a data perspective, it's an exciting time.”
Agus believes that the world is at an inflection point—we’ll either adapt and succeed wildly, or fail to adapt and cause real harm. “We have to be transparent about how the data is structured, how we use the data in today's world, because you can use it for wrong,” said Agus. Medical researchers need to ensure that they’re studying diverse communities, and avoid the mistake of assuming that data from one population necessarily holds true for other groups of people. “We’ve never before gotten results this quickly, but that was all because of data collection systems, data analytics systems, and structured data,” said Agus. “We’ll go forward now using real-world evidence data.”
Illustration: Wes Rowell