Digital oncology navigation based on ePROs: Effects on acute healthcare utilization and cost savings in a middle-income country setting.

11111 Background: Oncologic treatment is associated with a high clinical and economic burden. Traditional patient navigation models often lack real-time symptom monitoring, increasing the risk of clinical deterioration. Digital navigation models incorporating ePROs have emerged as a promising strategy to address this gap. However, evidence on their implementation in low- and middle-income settings remains limited. This study aimed to assess the healthcare utilization and economic impact of an ePRO-based digital oncology navigation program in a real-world Brazilian healthcare setting. Methods: We conducted a prospective, single-arm, before-and-after study between February and November 2025 at a private healthcare provider in southern Brazil. Adult patients (pts) with any cancer type undergoing intravenous chemotherapy and/or immunotherapy were enrolled in a digital oncology navigation program integrating app-based ePRO monitoring, automated symptom triage, and proactive nurse-led follow-up. The primary outcome was estimated cost avoidance (from the healthcare provider perspective), calculated as the difference between pre- and post-implementation costs associated with acute healthcare utilization (hospitalizations and emergency room [ER] visits). Secondary outcomes included hospitalization and ER utilization rates, patterns of digital health service use (program adherence and daily and overall volume of symptom reports), and the clinical profile of pts who required hospitalization. Descriptive statistics were applied. Results: A total of 55 pts were included. The mean age was 54 years, and 63.5% were female. Breast cancer (25.5%; n = 14), non-Hodgkin lymphoma (12.7%; n = 7), and lung cancer (10.9%; n = 6) were the most frequent tumor types. Most pts had stage II–III disease (63.9%) and were receiving chemotherapy (54.8%). Hospitalization rates decreased from 29% to 22% after program implementation, while ER utilization declined from 80% to 35%. Patient adherence was high (90.8%), with consistent engagement in symptom reporting throughout follow-up (600 total symptom reports; mean of 5.4 daily reports). Most reported symptoms were managed remotely by the nursing team (95%), with minimal need for physician escalation. Among pts who required hospitalization, lung cancer was the most frequent primary tumor (50.1%). The estimated total cost avoidance was R$332,769 (≈US$66,500), corresponding to a mean saving of R$6,050 (≈US$1,210) per pt. Avoided hospitalizations accounted for most of the economic benefit. Conclusions: Implementation of an ePRO-driven digital oncology navigation program may reduce acute healthcare utilization and meaningful short-term cost avoidance in a real-world healthcare setting. These findings support the integration of digital symptom monitoring as scalable, cost-saving strategie in oncological care delivery.