What if health care organizations could identify and engage patients at risk for severe COVID-19 complications before they got sick?
In Philadelphia, teams at Einstein Healthcare Network are making it happen. They’re working with Cerner to run an open-source model1 that predicts patients’ COVID-19 complication risk, then they’re proactively engaging vulnerable individuals to help keep them safe.
Jason Aronovitz, DO, director, population health analytics, enlisted help from Cerner teams to run the model in HealtheDataLab™, the Cerner data science ecosystem. Less than two weeks later, Aronovitz had a list of patients for outreach, prioritized by risk.
“We have the infrastructure in place to manage care for high-risk patients in our accountable care organization (ACO),” Aronovitz said. “When COVID-19 came, we pivoted those resources to proactively engage vulnerable individuals with services.”
HealtheDataLab provides tools and an environment to run the predictive model using Einstein’s patient data from Cerner HealtheIntent®. The model considers factors like the patient’s age, recent hospital visits and the presence of diagnoses associated with COVID-19 complications to generate their COVID-19 risk score.
Einstein’s care management team members target high-scoring—or at-risk—patients with proactive outreach, providing education on COVID-19 symptoms, prevention strategies and what a patient should do if they feel unwell. The staff convert existing patient appointments to telephone visits or schedule new appointments if needed. They also help patients source necessities like food or medication and support patients’ emotional health needs by discussing stressors, encouraging connection and scheduling follow-up calls.
Einstein staff members began COVID-19 outreach a couple weeks before implementing the open-source model; adding the predictive model helped focus and expedite their efforts.
“Cerner’s expertise in HealtheDataLab and the ability of HealtheIntent to turn around report requests quickly has been helpful,” Aronovitz said. “We originally had about 30,000 people on our outreach list. Adding the risk index helped us prioritize outreach. We use the risk score as our primary guide and divide the list geographically by ZIP code, knowing which areas have the highest rates of COVID-19 infection based on data from state and local public health departments.”
Aronovitz and his team plan to continue collaborating with Cerner to explore opportunities for automating and expediting proactive outreach to vulnerable populations.
“Managing population health in a pandemic is new for everyone,” Aronovitz said. “There’s a lot of trial and error. You must quickly establish trust and get the data out there in a usable format. Communicating and asking for help have been keys to our success.”
Einstein leaders see improving COVID-19 outcomes as their immediate goal. But they also appreciate the project’s potential to strengthen relationships throughout the organization’s Philadelphia community, as a trusted partner helping patients manage their well-being.
“We have a great team willing to help,” Aronovitz said. “Patients appreciate us offering support during this crisis and educating them.”
As the world responds to the COVID-19 pandemic, Cerner’s work continues to support health care providers and communities across the globe. Learn more here.
1 https://github.com/closedloop-ai/cv19index
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