Emerging Technologies Fostering Digital Business Innovation: Healthcare

Healthcare is evolving under simultaneous pressures: rapid innovation in research and treatment, the ongoing digital transformation of operations, socio-economic barriers to access, and shocks such as COVID-19. Several technology-driven trends are emerging: precision health and self-service care models, broader access to interoperable data, and more accessible diagnostics as costs fall—accelerated by AI, blockchain, IoT, and digital identity. Precision health reframes care as personalized, proactive, and outcome-oriented, supported by wearables, implantables, and AI-driven prediction.

A persistent barrier is the lack of standardized, interoperable electronic health records (EHRs), limiting cross-institution referrals, insurance communication, and data aggregation. This data fragmentation also constrains the sector’s ability to respond to public health crises and to leverage growing volumes of structured and unstructured data from EHRs and digital imaging.

AI is positioned as both a patient-facing and operations-facing engine: chatbots and NLP tools can increase access to guidance and triage; image classification supports diagnosis and early detection; analytics improve clinical workflows (including chart review and clinical trial recruitment); and hospital optimization uses forecasting and automation to reduce waste (e.g., predicting appointment no-shows). However, healthcare AI requires heightened governance due to direct safety risks, limited explainability, and bias in training data that is often Western-centric and not representative.

Blockchain’s clearest near-term value is drug tracing and selective anchoring of trustworthy records, while patient-controlled records and medical credentialing may deliver benefits but can often be met with traditional architectures. IoT adoption is high (IoMT), spanning wearable, implantable, and ambient sensors, but introduces serious security and interoperability challenges. Digital identity emerges as foundational infrastructure to enable patient-centered interoperability, device access control, and efficient workflows, while avoiding identity friction that could delay care.

• SDG Goal 3 is defined as “Ensure healthy lives and promote well-being for all at all ages.”
• World Health Statistics 2020 finds that country health information systems are severely lacking, and gaps in relevant health data can slow or inhibit timely public health crisis response.
• The EU issued a 2011 directive establishing citizens’ rights to cross-border healthcare, driving efforts to standardize EHRs.
• A US mandate took effect in 2014 requiring health practitioners to use electronic health records.
• Appointment no-shows range from 5%–15% of all appointments, depending on the hospital.
• In 2018, an AI-based image classification system for diabetic retinopathy became the first AI diagnostic system to receive US FDA approval.
• IoT connectivity options discussed include WiFi, cellular networks, Bluetooth, and LPWANs, each with tradeoffs in energy, range, and bandwidth.
• LTE-M and NB-IoT are identified as suitable for conserving power in long-life IoT applications with low bandwidth requirements.
• GDPR went into effect in May 2018.
• IEC 62304 specifies requirements for medical device software development and lifecycle processes, including acceptance of software of unknown provenance (SOUP).

• “The rate of progress that has been made up to 2020 is not sufficient to meet the goal by 2030 unless solutions are improved and rapidly scaled up to meet the needs of the global population.”
• “It is anticipated that AI-supported health services will significantly reduce diagnostic costs, drastically increasing the number of people who have access.”
• “Precision healthcare will become a defining business model of the industry.”
• “Patient-centered interoperability recognizes that patients are owners of their health data, and should be active participants in their health journey.”
• “However, there must be stronger ethical guidelines to govern AI development for the medical field, as the risk of damage from misuse or improper training is very high.”
• “Explainability, particularly when the decisions impact medical advice or care, is extremely important and still lacking.”
• “Blockchain has the potential to help the healthcare industry become more patient-centric and operate less in institutional silos.”
• “For a blockchain solution to deliver reliable information, the input data must be accurate.”
• “IoT in healthcare is generally highly accepted, with several popular commercial products such as fitness watches being viewed as ‘normal’.”
• “Digital identity is the next essential digital transformation step for the healthcare sector.”