How COVID-19 Is Changing Health Care

From a lack of access to high costs to sometimes-subpar care, complaints about the U.S. health care system aren’t exactly a new topic. But the coronavirus pandemic has thrown the long-standing and chronic deficiencies of the system into sharp relief, highlighting built-in inequities like never before, says a leading researcher in information systems—and it’s likely to spark some lasting changes.

“COVID-19 was the health care system’s wake-up call, reminding us of the underfunded and inadequate public health infrastructure, the inability to capture, analyze and share data to make timely and evidence-based decisions, the deeply disturbing health care apartheid in society, and the enormous price tag associated with the system,” said Distinguished University Professor Ritu Agarwal, senior associate dean in the Robert H. Smith School of Business.

The pandemic has pushed conversations about the issues in new directions, said Agarwal, the Robert H. Smith Dean’s Chair of Information Systems and co-director of the Center for Health Information and Decision Systems. There’s growing consensus on the need for greater use of digital technologies and data to lubricate decision making and break down silos. 

“Digital health care may finally have reached a tipping point,” she said.

Agarwal predicted that two technologies in particular will remain “sticky,” post-COVID:

Telemedicine: While the basic technology has been with us for a while, its use in health care had never caught on in the United States—until there was no other choice.

“Health care workers’ safety, patients’ inability to travel because of COVID restrictions, and a growing patient volume necessitated a quick pivot from the traditional in-person health care encounter to a virtual visit enabled by telemedicine,” Agarwal said. 

Telehealth use might have been adopted as a temporary solution, but it will continue as a central tool, she said, as patients have become increasingly comfortable with virtual visits and providers have learned to utilize them more effectively. 

“Telemedicine can reduce costs, mitigate inefficiencies and perhaps make health care more accessible and available to vulnerable and underserved populations,” she said.

Artificial intelligence (AI): This technology is emerging and evolving, said Agarwal. But AI, and in particular, a variant known as machine learning (ML), is already beginning to transform health care. 

“AI offers the promise of enabling greater leverage of one of the scarcest resources in health care: clinical knowledge and expertise, while also supporting efficiencies and improving quality and consistency in care delivery,” she said. 

Machine learning, or the ability for systems to learn automatically from data, had already demonstrated robust potential pre-pandemic for helping get handle on a health care system drowning in all manner of data, catching the attention of doctors, hospital systems, and insurance companies. 

The pandemic sparked many applications using AI and ML—for example, predicting the risk of becoming infected so hospital workers can triage patients more effectively, or forecasting the emergence of new clusters of infection.

Post-pandemic, attention will shift to continued exploration of where AI/ML offers the most utility and value in areas like medical image analysis, pattern detection and new clinical discoveries in medical charts, as well as greater personalization of medical interventions. 

“We have just scratched the tip of the iceberg,” Agarwal said.