Healthcare and life sciences
Patient and research data governed by GDPR and medical confidentiality.
Context
Hospitals, insurers and life sciences companies hold the most sensitive category of personal data. AI offers substantial relief on documentation and research, provided the data never leaves a controlled environment.
Key regulation
| Framework | Relevance |
|---|---|
| GDPR | Health data is a special category under Article 9, with strict conditions for processing. |
| EU AI Act | AI in regulated medical devices is high-risk, with obligations applying from 2 August 2028. |
| NIS2 | Healthcare providers are within scope of the cybersecurity regime. |
| European Health Data Space | Sets rules for the use and secondary use of electronic health data across the EU. |
Challenges and opportunities
Challenges
- Special category data Patient records require a lawful basis and safeguards beyond ordinary personal data.
- Clinical accountability Outputs used in care must be traceable, reviewable and validated.
- Procurement Public tendering rules shape which providers and models can be selected.
Opportunities
- Clinical documentation Drafting and summarising records, referrals and discharge letters.
- Research acceleration Analysis of research data within the institution's own environment.
- Patient communication Clear, multilingual information drafted under clinical supervision.
How Lindstead helps
- AI strategy Define which workloads require in-house deployment and which remain suited to external APIs, with a clear board recommendation.
- Regulation and risk Map data flows, access rights and the resulting obligations under the AI Act, GDPR, DORA and NIS2 across the organisation.
- Model selection Identify the models best suited to each use case, assessed on performance, language coverage, licensing terms and provenance.
Discuss the priorities in healthcare and life sciences.
Schedule an introductory meeting with our team.