Digital health integrates digital technologies with health care to improve prevention, diagnosis, treatment and long term management of disease. It spans telemedicine, mobile health apps, wearable sensors, artificial intelligence, big data analytics and digital therapeutics.

Research highlights how digital health can increase access to care, especially for people in remote areas or with limited mobility. Teleconsultations and remote monitoring allow continuous follow up, reduce hospital visits and may lower costs. Wearable devices and smartphone apps enable real time tracking of vital signs, physical activity, sleep, glucose levels or cardiac rhythms, generating high frequency data that can reveal early signs of deterioration or disease onset.

Artificial intelligence models trained on large clinical and sensor datasets can support diagnosis, risk prediction and personalized treatment decisions. Examples include algorithms for detecting arrhythmias from wearable ECGs, identifying lesions in medical images and forecasting exacerbations in chronic conditions. Digital therapeutics deliver evidence based behavioral or cognitive interventions through software, such as programs for managing diabetes, cardiovascular risk, mental health disorders or chronic pain.

Studies emphasize the need for rigorous clinical validation, interoperability between systems and robust data governance. Key concerns include privacy, cybersecurity, algorithmic bias and unequal access to digital tools. There is active work on standards, regulatory frameworks and methods for integrating digital health solutions into routine clinical workflows without overburdening professionals.

Overall, research suggests digital health can shift care toward prevention, early detection and patient self management, while enabling more precise and data driven medicine. Its success depends on careful evaluation, ethical deployment and attention to equity and user centered design.