Disruption in healthcare has been a long time coming, and for many organizations, the COVID-19 pandemic acted as the catalyst to adopt innovative technologies.

For instance, even some of the most cutting-edge health systems only had artificial intelligence and machine learning programs for a few years prior to the onset of the pandemic.

“Children’s Hospital of Colorado has a rich history of leveraging data and information to support decisions, but until about three and a half years ago it was siloed and spread across our organization in seven-plus different areas,” Kerri Webster, CPHIMS, MS, RN, vice president at Colorado Children's, said today at HIMSS21.

Since Webster joined Colorado Children’s in 2020, the organization has taken its fragmented analytics team and created one unified division that supports the decision-making and data reporting for the entire system.

“When COVID hit, it was like ‘we can’t do without this now,’ and it really became a cornerstone for how they were making decisions,” she said.

That experience was similarly felt at many health systems across the nation, including at the Parkland Health and Hospital System in Dallas.

Although its data science programs began back in 2010, Vikas Chowdhry, the chief analytics and information officer at the Parkland Center for Clinical Innovation says the pandemic has led it to grow its capabilities leaps and bounds.

Today, Parkland uses AI and ML right at the bedside to help clinicians predict disease progression or to track sepsis in the community in order to help federally qualified health centers understand their patient population, and used them during the pandemic to help monitor outbreaks to manage its patient intake.

Providence health system leveraged data analytics in a similar fashion to create what Aaron Martin, the executive vice president and chief digital officer, calls “virtual PPE.” Using the system’s patient-facing chatbot, Grace, it assessed the risk of COVID-19 infection, answered patient questions and directed them to the appropriate venue of care.

At this point, health systems that haven’t yet adopted some level of digital health tools are falling behind, according to Martin.

“If you’re in a health system right now, like I am, you've got to really, really think about the level of investment you’re making in digital and how you’re doing it because it’s on,” he said. “You won’t know it until you feel it, but when you feel it, it’s going to be too late.”

Among those already on top of their digital game, the ways they leverage that technology will vary from organization to organization.

For instance, Colorado Children's uses AI and ML to ensure they have adequate staffing by predicting their future patient load.

“Our challenge has been to predict the future. It’s kind of like telling if it’s going to snow on Christmas Eve,” Webster said. “So we’re predicting about 18 months out, and so far our models have been within four to five patients.”

At Parkland, which has a large portion of Medicaid beneficiaries, its biggest AI and ML use-case is to promote health equity and improve access.

“The answer to that is not going to be building more physical buildings,” Chowdhry said.

Instead, it is using technology to better understand the characteristics of its patient population to create solutions that meet them where they are.

Similarly, Providence is using tech to create more personalized care options.

“If you don’t get [patients] to engage, it doesn’t really matter,” Martin said. “You can have the coolest, slickest automated telehealth capability, or async, or whatever, but if they don’t engage, it doesn’t matter.”

Stakeholder engagement is key to unlocking the biggest potential of AI and ML, according to the speakers, and to do so there must be a human element to these tools.

“The way we’ve found to be the most successful is to complement data with stories,” Chowdhry said. “In a lot of presentations when you’re talking with either stakeholders, clinicians or even to patients, yes, you want to have data to show that this is actually making an impact, but data can change minds [and] stories can change hearts.”