STORY / PUBLIC SOURCE RECORD
Cloud computing in healthcare
- Published 21 February 2025; updated 25 March 2026; estimated reading time 3 minutes. The article defines cloud computing as internet-delivered storage, processing and networking that lets users manage data without on-site infrastructure. It defines machine learning as a branch of AI that learns from data and improves prediction, and says combining ML with cloud services can help analyse large healthcare datasets for diagnosis, treatment planning and operations.
- Listed applications include cloud-hosted electronic health records that can be securely accessed and shared across care teams; telemedicine, remote monitoring and patient-engagement tools; analytics for patient outcomes, resource allocation and population-health trends; and shared research environments for real-time clinical collaboration.
- Benefits named are lower hardware/maintenance costs, scalable storage and processing, access for authorised staff from different locations, and security protections such as encryption and recurring audits by reputable providers.
- Challenges identified are privacy and regulatory compliance (including GDPR), integration with legacy systems/interoperability, service outages that can affect critical data and applications, and vendor lock-in that can reduce flexibility or complicate migration/multi-cloud use.
- The article also briefly discusses quantum computing as a possible future complement for complex calculations, including large genomic-data analysis and research into genetic diseases. It links to Norwegian digital-health solutions and the Health and life science industry page.