Digital Health Ethics in Clinical Practice

Abstract

Digital health technologies -- electronic health records, clinical AI, telehealth platforms, wearable monitoring devices, patient-facing health applications, and increasingly large language model-based clinical assistants -- have transformed how healthcare is delivered but have simultaneously generated ethical concerns that conventional medical ethics frameworks address incompletely. Privacy implications of continuous health data collection, informed consent adequacy when data uses evolve over time, algorithmic bias effects on care equity, clinician-patient relationship changes from digital mediation, and accountability questions when AI contributes to clinical decisions all represent ethical domains where established bioethical principles need extension or reinterpretation for digital contexts. We evaluated five digital health ethics governance frameworks applied to 186 digital health deployments across 22 European clinical networks between 2019 and 2024, spanning EHR analytics, clinical AI, telehealth, wearable monitoring, and patient-facing applications. Frameworks ranged from general institutional ethics oversight through integrated digital health ethics governance with ongoing patient advisory input, algorithmic audit infrastructure, and regulatory compliance integration. Performance was benchmarked using our Digital Health Ethics Effectiveness Score (DHEES), integrating consent and autonomy, privacy protection, equity assurance, accountability clarity, and patient trust. The integrated governance framework achieved the highest DHEES (0.912), with patient trust scores of 8.4/10 versus 4.2/10 under general oversight frameworks, and documented ethics incident remediation in 78.4% of identified cases versus 24.6%.