Integrating Digital Health into Oncology: A Comprehensive Review

Background/Objectives: Digital health encompasses telemedicine, mobile health (mHealth), wearable technologies, big data analytics, artificial intelligence (AI), machine learning (ML), and immersive technologies. In oncology, where care is complex, multidisciplinary, and longitudinal, these tools offer opportunities to enhance prevention, early detection, treatment planning, patient–clinician communication, survivorship, and palliative care. However, inconsistent definitions and ongoing ethical, regulatory, and implementation challenges hinder optimal integration. This review aims to synthesize current evidence on digital health in oncology and examine its applications across the cancer care continuum. Methods: A comprehensive narrative review of peer-reviewed literature was conducted, including clinical studies, trials, and systematic reviews evaluating digital health technologies in oncology. Evidence was organized according to key phases of the cancer care continuum, from prevention and diagnosis to treatment delivery, survivorship, and end-of-life care. Results: Digital health applications extend beyond virtual consultations. AI- and ML-driven systems support diagnostics, medical imaging, genomics, and treatment planning, while mHealth applications and wearable devices enable real-time symptom monitoring, toxicity reporting, and long-term follow-up. Digital education and communication platforms improve shared decision-making and patient engagement. Across diverse oncology settings, these tools demonstrate feasibility, high patient and clinician satisfaction, and potential improvements in care coordination and efficiency. Nevertheless, challenges related to data quality, interoperability, privacy, algorithmic bias, equity of access, and regulatory oversight persist. Conclusions: Digital health is increasingly embedded across the oncology care continuum and holds substantial promise for advancing personalized, patient-centred cancer care. Continued multidisciplinary collaboration, robust clinical validation, and responsible governance are essential to ensure safe, equitable, and clinically meaningful global implementation.