AI in healthcare — what gets approved in Japan
Hospitals, clinics, pharmaceutical and device companies in Japan face two gating conditions before any AI deployment: how patient health information is handled, and compliance with the medical information system security guidelines issued jointly by the Ministry of Health, Labour and Welfare, METI and the Ministry of Internal Affairs — known locally as the 3-ministry guidelines. This guide sets out how to weight the selection criteria, what compliance questions to expect, and which uses are realistic today.
Published · updated
What makes this sector different
Confidentiality of patient health information
Names, clinical details and prescriptions are sensitive personal information under Japan's Act on the Protection of Personal Information. Providing them to an AI vendor requires explicit consent, contractual protection and a clear answer on data residency — all three, not one of them.
Documentation volume and clinical workload
Electronic records, referral letters, discharge summaries and case reports are long-form and constant. Summarising and formatting is exactly what these models are good at, and it is where the administrative load on doctors and nurses actually drops.
The medical device software boundary
If AI performs diagnosis it becomes medical device software and requires PMDA approval. Document assistance, training material and internal Q&A sit outside that boundary and can be treated as ordinary business AI.
Dependence on overseas vendors
Incident response, terms changes and data jurisdiction all sit abroad. Whether there is a Japanese entity to contract with, and whether a Tokyo region is available, often decides whether a deployment proceeds at all.
Rules that apply
- The 3-ministry guidelines
- Security management guidelines for medical information systems (MHLW) and for service providers handling medical information (METI and MIC)
- Act on the Protection of Personal Information — sensitive information
- Medical history requires explicit consent; you need a documented consent scheme before data reaches an AI system
- Pharmaceuticals and Medical Devices Act
- Providing a diagnostic algorithm makes the software a medical device. Document assistance and training material generally fall outside this
- Record retention and the Medical Practitioners Act
- Retention requirements for clinical records, electronic signatures and tamper evidence
This is editorial summary, not legal advice. Confirm the current position with your own counsel before committing to a deployment.
How to weight the selection
Tools that tend to clear this bar
A starting shortlist, not an endorsement. Confirm certification, contracting entity and residency for your own jurisdiction before you commit.
Claude$20/mo
Long-context reasoning with careful, well-structured writing. Strong on drafting, research and design work.
- Commercial use OK
- Japanese UI
- Free tier
Microsoft Copilot$30/mo
AI across Microsoft 365: drafting, summarising and analysis inside Word, Excel and Teams.
- Commercial use OK
- Japanese UI
- Enterprise contract
DeepLPro from ¥1,200/mo
The benchmark for machine translation — the natural Japanese output is why teams here standardise on it.
- Commercial use OK
- Japanese UI
- Free tier
Fireflies.aiFrom $10/mo
The veteran meeting recorder: CRM sync, speaker analytics and topic extraction for teams.
- Commercial use OK
- Free tier
- Enterprise contract
Questions we get
- Can patient information go into an AI tool?
- As sensitive personal information it requires either anonymisation or explicit consent. A data processing agreement covering training exclusion, retention period and data residency is the baseline, and an internal policy should exist before anyone uses the tool.
- Are any AI tools certified against the 3-ministry guidelines?
- The guidelines do not certify tools; they place obligations on the organisation deploying them. In practice Microsoft 365 is the most common route because the compliance work exists at the platform level, and Claude appears via resellers with a Japanese contracting entity. The responsibility for compliance remains with the hospital or company.
- Where is the line with medical device regulation?
- Diagnosis is the line. Supporting documentation, summarising records, generating training material and answering internal questions are ordinary business uses. Anything that outputs a diagnostic conclusion needs regulatory review.
- What is the realistic first deployment?
- Documentation support — summaries, referral letters, meeting notes — on a tool with a Japanese contracting entity and training exclusion. It delivers measurable time savings without touching the regulatory boundary.