Virtual supportive oncology in a multi-speciality cancer network: demographic profiles, rural-urban utilisation patterns and operational performance

Objectives Virtual health has the potential to improve access to supportive oncology and improve operational performance; however, real-world data across multi-speciality cancer programmes are limited. This study evaluated virtual visit utilisation, operational metrics and patient demographics by rurality within a large supportive oncology network. Methods We conducted a retrospective analysis of all supportive oncology encounters (January 2021–December 2024) at a 10-site cancer network encompassing palliative medicine, senior oncology, integrative oncology and psycho-oncology. Operational metrics, including cancellation, no-show, same-day and 3-day access, were compared between virtual and onsite visits using two-proportion z-tests (n=45 777). Demographic characteristics (gender, race, age, payer) of unique patients (n=6722; July 2023–December 2024) were compared across rural, suburban and urban categories using χ 2 tests. We assessed patient satisfaction using National Research Corporation Health surveys. Results Of 45 777 encounters, 14 353 (10.1%) were virtual and palliative medicine comprised 33.6% of these visits. Virtual visits had lower cancellation rates (23.0% vs 38.0%; absolute difference −15.0 percentage points (95% CI −16.3 to −13.7); p<0.001) and higher same-day access (15.0% vs 8.0%; p<0.001) than onsite visits. Urban patients represented 89.7% of virtual users. Significant differences in gender, race, age and payer mix were seen across rurality categories (all p≤0.004): rural patients were more frequently male (39.9% vs 30.9%), White (77.3% vs 63.3%) and Medicare-covered (54.1% vs 46.8%) compared with urban patients. Patient satisfaction was 94.3% “likely to recommend.” Conclusion Virtual supportive oncology demonstrated superior operational performance compared with onsite visits and was used primarily by urban patients with high symptom burdens. These findings suggest that convenience and clinical need, rather than geographic distance, drive adoption. Demographic differences across rurality should inform equitable programme development, including targeted outreach to underrepresented non-urban populations.