Background: In 2016, the National Academy of Sciences, Engineering and Medicine convened a workshop to examine challenges patients experience accessing specialized nutrition care in outpatient cancer treatment settings. Inadequate Registered Dietitian Nutritionist (RDN) staffing and reimbursement were identified as barriers to timely care. Staffing challenges at our three destination community cancer centers led to a backlogged queue of nutrition consults resulting in a ≥ 4-week wait time for an appointment. A quality improvement project to address delays in care for patients at risk for malnutrition, resulted in implementation of a hybrid model utilizing remote RDNs to provide virtual Medical Nutrition Therapy (MNT) to supplement onsite RDNs. Methods: After approved in June 2022, two remote RDNs were hired to provide virtual patient care. Nationwide recruitment allowed for hiring rare talent. A project team was created to assure we followed all regulatory guidelines related to licensing and billing. RDNs were individually licensed in 14 states to cover where ≥ 70% of our patients reside. System-wide criteria and licensure alerts for appointments were established between scheduling and nutrition leaders. The first patients were seen virtually on October 14, 2022, with units of service (uos) logged in 15-minute increments. Results: Appointments were tracked from October 14, 2022, through February 3, 2023. 69.2% of 302 scheduled appointments were successfully delivered virtually via telehealth platform with a mean of 1.7 uos. The main reasons for nonuse of the platform were no shows (52.7%) and the need to convert to a phone call (32.3%). The mean uos was significantly higher in new patients compared to returning patients (2.23 versus 1.53; p<0.001). Conclusions: A hybrid model of onsite and virtual care RDNs has potential to improve access to nutrition care. New patient appointments averaged > 30 minutes, and follow-ups averaged < 30 minutes. This may help inform future scheduling of virtual MNT appointments. This model may allow for recruitment from a wider pool of RDNs. It may also help avoid delays in care for patients at risk for malnutrition and gaps in their cancer treatment.

*P ≤ 0.05.