Digital health technologies in oncology services: A scoping review of clinical implementation, organisational...

Digital health technologies are increasingly used across oncology services, but the available evidence remains concentrated on patient-facing and clinical applications. Organisational perspectives and the involvement of non-clinical professionals remain poorly represented. This scoping review mapped digital health technologies used in adult oncology care, examined their functions for healthcare professionals (HCPs), and assessed the extent and nature of evidence involving non-clinical professionals (NCPs).

A scoping review was conducted to identify studies reporting the use of digital health technologies in adult cancer care. PubMed, Embase, CINAHL, and Web of Science were searched for studies published between 2015 and June 2025, and reference lists were hand-searched. Qualitative, quantitative, mixed-methods, pilot, feasibility, and implementation studies were eligible. Findings were synthesised narratively according to the primary function of each technology and the professional groups involved.

Forty-one studies were included. The most frequently reported technologies were electronic patient-reported outcome systems, telehealth and telemonitoring platforms, mobile applications, and decision-support or AI-enabled systems. These technologies were used mainly for symptom monitoring, communication, follow-up, survivorship support, clinical decision support, and care coordination. Reported benefits included earlier symptom detection, improved communication, greater patient reassurance, and more structured clinical workflows. Common barriers included limited digital literacy, declining engagement over time, alert burden, workflow misalignment, poor interoperability, and inadequate technical infrastructure. Only three studies explicitly included non-clinical professionals, indicating that organisational and managerial applications remain substantially under-researched.

Interoperability and workflow integration emerged as the most consistently supported implementation priorities. Equity, scalability, sustainability, and economic impact require further evaluation. Because evidence involving non-clinical professionals and AI-enabled implementation remains limited, recommendations concerning organisational adoption, AI governance, and workforce preparation should be treated as priorities for implementation research rather than established policy requirements.