JMIR Publications

ABSTRACT

The rapid advancement of AI-driven diagnostics and wearable health technologies is revolutionising healthcare delivery by enabling real-time health monitoring and early disease detection. This paper explores the current National Institute for Health and Care Excellence (NICE) Evidence Standards Framework (ESF) guidelines and evaluates the barriers to integrating Digital Health Technologies (DHTs) into the existing health and care system. These innovations are driving a shift towards personalised medicine, where interventions are tailored to individual patient profiles with unprecedented precision. NICE developed the ESF for DHTs to provide clear and consistent guidelines for assessing the efficacy, safety, and economic value of new digital health innovations. This paper posits that the NICE ESF should undergo strategic updates to remain relevant and effective in the face of rapidly advancing technologies, particularly those that evolve continuously through machine learning and real-world data integration. We propose that the NICE ESF transitions to a more dynamic, adaptive model, co-designed with industry partners to incorporate real-world evidence strategies. By promoting transparency, efficiency, and collaborative innovation, the framework can better support the integration of AI-based diagnostics and wearables into healthcare systems, ultimately improving patient outcomes and optimising healthcare performance.