How Mount Sinai Took a Data-Driven Approach to Health Equity

If you ask Lynne Richardson, MD, the road to health equity is paved with data.

The emergency medicine doctor is also a founding co-director of the Institute for Health Equity Research at the Icahn School of Medicine at Mount Sinai, which has worked closely with the institution’s health equity Task Force to enable data-driven change.

In the three years that have passed since COVID-19 and George Floyd’s murder created a cascade of promises to promote anti-racism and health equity, Richardson said Mount Sinai has put its money—or its research and data—where its mouth is.

“What's special about what's happening at Mount Sinai is that there actually is this very detailed plan with a set of strategies that are being implemented to really look at every aspect of the way the organization does business,” Richardson, who is a professor of emergency medicine, population health science and policy, and artificial intelligence and human health at Icahn, said in an interview.

Mount Sinai’s work toward health equity started as a confluence of organization stakeholders working toward the common goal of becoming “an anti-racist health care and learning institution that intentionally addresses structural racism,” Sinai leaders wrote in a recent paper detailing their health equity work to date.

A 51-member Task Force to Address Racism first set out to create a Roadmap for health equity, working to create a unified system-wide approach to rooting out racism in the institution. The Task Force finished the Roadmap in March of 2021 and has been working to implement it system-wide ever since.

According to Richardson, this effort is unique from other promises for health equity because it is fundamentally data driven.

“As you know, healthcare quality is measured all the time. We have hundreds of quality metrics,” she explained. “We have it for every patient, every organization, every specialty, every condition.”

That, coupled with Mount Sinai’s good performance in collecting race, ethnicity, and language (REL) data, gives the organization the ability to look at its quality metrics as a function of sociodemographics.

For example, Richardson and her team might find a disparity in some process measure, like a preventive screening or a flu shot.

“If it turns out that a different percentage of your Black patients compared to your White patients are getting a required health preventive service, that's something we have to figure out,” she said. “Why is that different, and what do we have to do to get everyone the same access?”

Is it that there’s an access issue? Is the service only offered during traditional office hours? Is there a months-long waiting list that may discourage access? Through that deeper dive, Richardson said Mount Sinai can determine strategies to level the playing field for all patients. Maybe it’d be better to offer community-based vaccinations or offer a service during off-hours, too.

“The clinical leadership of the health system has taken this on with a willingness to look at the data and then, when we find something in the data, to think together about the interventions to actually correct this,” Richardson stated.

But it’s more than just the leadership, she added.

This data-driven approach has been crucial to cultivating the buy-in of frontline clinicians, nearly all of whom genuinely believe that they provide the same level of care to all their patients. While the good intentions of doing so may be present, Richardson said the data simply can’t support the notion that health equity has been achieved.

“The first thing is really about looking at the data because most people believe they're doing the right thing and most of them have never looked at the data to see whether or not that's actually born out,” she explained.

“You actually have to look at your data to see if, in fact, you are treating everyone the same and, more importantly, if people are having the same outcomes,” Richardson continued. “And then we get into the conversation about the difference between treating everyone identically and treating everyone equitably.”

By tapping into data science, she can illustrate to providers where health disparities emerge. And by using concepts like risk stratification and adjustment, it’s easier to make the case for health equity.

Getting to this data-driven approach is not easy, Richardson admitted. While healthcare does have a vast system in place to measure clinical quality, not every organization is equipped to break down those quality measures by sociodemographics. That’s because the capture of that REL data is limited. Some assessments have put REL data capture as low as 18 percent.

While there are some hiccups with data infrastructure standing in the way, Richardson asserted that most organizations don’t have high REL data collection rates because collecting that information can be uncomfortable. Some registrars are hesitant or fearful they may offend a patient.

Mount Sinai has scripted the REL capture process, equipping registrars and other stakeholders with responses if patients push back. By telling patients everyone gets asked about their race, ethnicity, and language preferences, Richardson said the organization has successfully overcome most of the discomfort of having that conversation upon intake.

“With properly trained staff, you can ask these questions, and patients will answer them, and then you'll have the information you need to really see how you're doing with equity,” Richardson explained.

Sinai isn’t just concerned about anti-racism in the clinical areas of its business, Richardson added. The Health Equity Roadmap looks at personnel and mentorship, evaluating data to ensure there is equity in that domain.

What about the supply chain? How many Black- or minority-owned businesses does Mount Sinai purchase from? And how can the organization reconsider its purchasing decisions equitably?

By reframing its business goals through a health equity lens, Richardson said Mount Sinai can serve truly as an anchor institution rather than a group of hospital workers trying to do the same right thing. And it’ll take a data-driven approach, she added, although it is taking the organization some time to coalesce around an expansive set of key performance indicators.

That is because there are many stakeholders in this work to become an equitable anchor institution, and Mount Sinai’s leadership team wants to ensure KPIs come from each department themselves. Richardson indicated that KPIs should come closer to the end of the calendar year.

Once those are in place, Richardson said Mount Sinai should be ready to take a big step forward. While she said she hesitates to make health equity out to be a numbers game, she asserted that being able to measure health equity across all lines of business is essential.

“We can drive behavior and we certainly can monitor behavior by collecting data,” she explained. “Then, there are lots of levers that we can push, both carrots and sticks, to get people to exhibit the behavior that we're looking for in terms of the way it impacts equity throughout the organization.”

And it’s not just about Mount Sinai’s road to health equity. Richardson said the organization hopes its roadmap can be a launching point for other organizations.

“The work we're doing really will be able to create a blueprint for other healthcare organizations,” she concluded. “This is how you do it. If you're serious about equity and being an anti-racist organization, this is what it looks like.”