In February 2020, hospital operations expert Carri Chan was in the eighth month of her yearlong sabbatical, embedded at NewYork-Presbyterian Hospital (NYP).

She had been studying a topic she says is right up her alley–the use of data and analytics to help understand and solve real-life challenges in hospitals. Chan was spending her days collecting data and trying to better understand factors that impact access to care, such as nursing levels, all at the deliberate pace that defines her typical research.

“Everything was moving along normally,” Chan says. “Then all hell broke loose.”

As the COVID-19 pandemic emerged as a national threat, the allocation of equipment and space became an immediate concern, and anyone with knowledge of how hospital supply chains worked was being called on for their expertise.

Chan, an associate professor in the Decision, Risk, and Operations Division, had been following the spread of COVID-19 from its early hotspots in Wuhan, China. But once Italy became gripped by infections in March, she knew that cases would soon be widespread in the United States. When New York City debated imposing lockdown orders in mid-March, it became clear to her and the team at NYP that they had a big logistical problem on their hands.

“People on the team were trying to figure out what rooms could be transformed into ICUs,” Chan recalls. “It was a hectic time and I really applaud the leadership at NYP.”

As an increasing number of patients arrived at the hospital, the entire staff sprang into action. Nurses who had transitioned into administrative roles began to treat patients again. Those who hadn’t put their EMT training to use in years were called on to help with incoming COVID-19 cases. “It was remarkable,” Chan says.

A NewYork-Presbyterian Hospital ambulance entrance on May 18, 2020. Photography: Noam Galai/Getty Images

On each of those early days, Chan participated in calls with members of the hospital management team who asked her to create models based on daily reports on patient admissions, how many ventilators were available, and how many beds were free. The goal was to develop strategies to deploy their resources in the most effective way to meet a growing influx of patients.

The frenetic pace of the hospital response forced Chan to shift her mindset from that of an academic trained to be as precise as possible, to that of an analyst expected to make predictions about the potential results of crucial decisions.

“We had to get information out as fast as possible,” Chan says.

“It was better to have reasonable, but not fully vetted, information than no information at all.”

Having Chan as part of the team during this time proved to be a significant help to the hospital, says Emme Deland ’80, the senior vice president for strategy at NYP, who adds that Chan’s explanation of the pros and cons of her models were articulate and transparent.

“Carri’s analyses provided important ‘aha’ moments as we tried to understand the ebb and flow of the surge,” Deland says.

To make her daily recommendations, Chan drew on findings from a 2015 study into a potential flu-like pandemic that demonstrated that a lack of staff tends to be the largest bottleneck in a hospital’s response. Her operational expertise allowed her to understand the implications of these finding for the COVID-19 pandemic.

“You can have an infinite number of beds and ventilators,” Chan explains. “But if you don’t have the people to care for patients, it’s useless.”

As cases increased in the hospital, Chan provided models to forecast the impact of personal protective equipment (PPE) availability—or the lack thereof—on the availability of doctors, nurses, and other staff.

“Everyone understood there would be negative consequences of limited PPE on the likelihood of staff getting sick, which in turn would impact the number of patients they could care for,” she says. “I quantified and demonstrated how big an effect it would have.”

“The hospital never ran out of beds, but you could see all the changes that were made. They were able to take care of everybody, but you could see it was very stressful.”

—CARRI CHAN

While NYP had to cancel elective surgeries and repurpose ventilators typically slated for short-term use for long-term care, NYP never reached its capacity for beds during the spring when cases spiked throughout the city.

“The hospital never ran out of beds, but you could see all the changes that were made,” Chan says. “They were able to take care of everybody, but you could see it was very stressful.”

Doctor Michelle Gong, the chief of pulmonary and critical care at Montefiore Medical Center in the Bronx and one of Chan’s research collaborators, says Chan’s approach to using data and modeling helps identify stress points in the medical system.

“Carri is at the forefront of understanding healthcare systems, which helps providers and clinicians with their medical decision-making,” Gong says.

It’s unlikely that Chan’s experience at NYP in the spring would have happened if not for a change of direction, just as she was embarking on her academic journey.

When Chan was growing up 30 miles outside of Boston, in Lincoln, Massachusetts, it wasn’t hospitals, but engineering that drove her early academic career. She stayed close to home for college, earning a degree in electrical engineering from MIT. She then left for Stanford but remained in the field for post-graduate work, earning a master’s degree and a doctorate in electrical engineering.

While in Palo Alto, Chan began researching the emerging field of wireless communications, studying the use of multimedia platforms and developing algorithms to improve the quality of streaming video.

Although Chan knew it was cutting-edge work, she soon became dissatisfied with the world of pixels and streaming.

“I wanted to do something where I felt I could have a big impact and help better the world,” she says.

Around the same time, Chan’s advisor at Stanford asked if she could help a physician at Kaiser Permanente with predictive analytics to assist the healthcare system in handling a resource shortage.

Chan agreed, but explained to the physician that her true expertise was not in machine learning, but resource allocation in random environments. The experience made her realize that instead of studying fluctuations in the signal strength of wireless channels, she could use similar models to move patients through a hospital more efficiently.

“It sounds like they are far apart, but methodologically, a lot of the tools are applicable to both subjects,” Chan says.

Ever since that first Kaiser Permanente project, Chan’s focus has been on healthcare, an industry that has historically suffered from a high degree of inefficiency. While the industry has made tremendous strides in improving operations, there is still work to be done, and Chan is eager to contribute.

“There has been a huge transition over the past five to 10 years in the growth of data availability,” Chan says. “There is an increasing openness to technology and data to guide and improve efficiency. The opportunity to make an impact and actually help people’s lives really appeals to me.”

Chan sees her time at NYP during the early months of the pandemic as part of a continuum with her previous research on efficiencies and hospital-resource allocation.

“I think it’s relevant in the COVID-19 setting,” she says. “People in the operations community, we have a methodological toolkit that allows us to answer fundamental questions across the board. We can use our tools to guide and understand the implications of decisions.”

Doctor Hayley Gershengorn, an associate professor of clinical medicine at the University of Miami who has co-authored research papers with Chan, says Chan is adept at communicating with medical professionals, asking insightful questions that lead to important operational interventions. “She speaks the language of a clinician,” says Gershengorn.

“The tools Carri is helping to develop will eventually become routinized in the way we manage ourselves,” Deland says.

“Carri’s work demonstrates to institutions the kinds of changes they can make without having to invest upfront,” Gershengorn adds. “She can tell us when we’re on the right track.”

Deland of NYP says that management decision-making in the healthcare industry is increasingly data driven.

“The tools Carri is helping to develop will eventually become routinized in the way we manage ourselves,” Deland says.

Chan brought her experience at NYP to bear in a Fall 2020 class on healthcare systems and strategies, and she’s written op-eds in the New York Daily News, NBCNews.com, Business Insider, and the Hill on hospital management during the pandemic. She continues to work on a project evaluating the New York State ventilator triage approach, should resources become scarce before a vaccine becomes widely available.

As someone who had an up-close look at the stress COVID-19 has put on the healthcare system, Chan says it’s vital that ordinary citizens do their part.

“We can’t let up with social distancing, masks, and washing hands,” Chan says. “It’s going to take time for a sufficient number of people to be vaccinated in order to get broad immunity. We’re not out of the woods yet.”