Diagnostics play a crucial role in screening, detecting, and stratifying patients, yet can account for only 2–3% of healthcare spending. With advancements in wearable technology and direct-to-consumer testing, the market for consumer health continues to rise. The potential benefits of more holistic and continuous measurement offer a promising opportunity for earlier disease detection and proactive health management. Many health systems are in a parallel transition from legacy analogue approaches to digitally enabled infrastructures. The evolving role of the clinical workforce, including medical ethics, regulation, will be closely coupled and a critical lever in success. This includes on a patient and clinician level, balancing the benefits and risks of interventions, and care pathway level, promoting responsible data utilisation with greater contextualisation based on the latest evidence of clinical efficacy. Moving forward a balance may need to be struck between increased data capture, analysis and reuse, with proportionate ethics, regulation, trust and governance.

Reliably processing and interlinking medical information has been recognized as a critical foundation to the digital transformation of medical workflows, and despite the development of medical ontologies, the optimization of these has been a major bottleneck to digital medicine. The advent of large language models has brought great excitement, and maybe a solution to the medicines’ ‘communication problem’ is in sight, but how can the known weaknesses of these models, such as hallucination and non-determinism, be tempered? Retrieval Augmented Generation, particularly through knowledge graphs, is an automated approach that can deliver structured reasoning and a model of truth alongside LLMs, relevant to information structuring and therefore also to decision support.

Digital health technologies (DHTs) can transform neurological assessments, improving quality and continuity of care. In the United States, the Food & Drug Administration (FDA) oversees the safety and efficacy of these technologies, employing a detailed regulatory process that classifies devices based on risk and requires rigorous review and post-market surveillance. Following FDA approval, DHTs enter the Current Procedural Terminology, Relative Value Scale Update Committee, and Centers for Medicare & Medicaid Services coding and valuation processes leading to coverage and payment decisions. DHT adoption is challenged by rapid technologic advancements, an inconsistent evidence base, marketing discrepancies, ambiguous coding guidance, and variable health insurance coverage. Regulators, policymakers, and payers will need to develop better methods to evaluate these promising technologies and guide their deployment. This includes striking a balance between patient safety and clinical effectiveness versus promotion of innovation, especially as DHTs increasingly incorporate artificial intelligence. Data validity, cybersecurity, risk management, societal, and ethical responsibilities should be addressed. Regulatory advances can support adoption of these promising tools by ensuring DHTs are safe, effective, accessible, and equitable.