Machine learning helps cancer center with targeted COVID-19 outreach

Regional Cancer Care Associates, based in New Jersey, has more than 20 locations throughout New Jersey, Connecticut, Maryland, Pennsylvania and the Washington area. Staff realized they needed a risk-stratified list of patients for COVID-19 vulnerability that nurses could manage through phone calls and by coordinating services with other providers. Because of staffing challenges, the list had to identify only the high-risk patients who staff needed to manage first, not the entire population or those patients who could wait a bit longer for nurse outreach. "Even though we already had an indigenous and independent scoring logic/mechanism for patient risk, this was mainly based on a combination of comorbidities that differentiated it from the usual scoring techniques," explained Lani M. Alison, vice president of quality and value transformation at RCCA. "Thus," she said, "there was a need to further stratify the risk patients for COVID-19 vulnerability and to establish a patient-centered assessment and outreach." On another note, staff observed challenges in assigning these patients and a defined patient roster to care coordination executives or support staff, which was hindering a patient-centric outreach approach, Alison added.