AI in patient education
AI-powered tools, including chatbots and virtual assistants, can offer personalised patient education and guidance.
Notable examples:
- Ada Health: AI-powered symptom checker providing educational insights on conditions.
- Woebot: A chatbot for mental health and chronic pain support.
- Phelix AI: Assists patients with physiotherapy-related FAQs and personalised exercise guidance.
Case study
A 50-year-old patient with chronic knee osteoarthritis struggled with self-management and exercise adherence. His physiotherapist introduced him to Omada, an AI-driven rehabilitation platform that used machine learning to create personalised exercise programs.
- Initial assessment: AI sought information from the patient including pain levels, and prior medical history to develop an individualised plan.
- Real-time adaptation: Based on patient feedback and compliance, the AI adjusted the intensity and frequency of exercises automatically.
- Instant feedback: The platform provided real-time feedback on exercise form, reducing the risk of incorrect movement patterns.
- Long-term progress tracking: AI continuously monitored adherence and progress, generating weekly reports for the physiotherapist.
Future of AI in patient education
AI is expected to continue evolving, with future developments likely to include:
- Voice-activated virtual physiotherapy assistants that guide patients through exercises with real-time corrections.
- AI-driven wearable devices that analyse movement patterns and predict potential injury risks.
- Deep learning models that generate hyper-personalised rehabilitation plans based on vast patient datasets.
