LibraryFamily 7 · Mental Health & Neurology
Self-referral assistant for NHS Talking Therapies
ValidatedActive deploymentDeveloping evidence
Formally validated with a published Assurance Pack.
Supports patient self-referral by collecting clinical information conversationally and routing referrals, reducing administrative wait time.
Plain-language summary
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Clinical context
- Clinical problem
- Support communication
- Point of care
- Pre-admission
- Nature of AI output
- A classification
- Clinical specialty
- Psychiatry
- Care setting
- Community care
- Patient population
- Adults self-referring to NHS Talking Therapies (IAPT) services for common mental health conditions.
- Intended use
- Supports patient self-referral by collecting clinical information conversationally and routing referrals, reducing administrative wait time.
Technology
- AI technique
- NLP / large language model
- Input data
- Patient-reported data
- Output type
- Classification
- Autonomy level
- Human in the loop (human acts)
- Model provenance
- Vendor proprietary
- Model version
- —
- Built on a general-purpose model
- Yes
Deployment
- Status
- Active deployment
- Country
- United Kingdom
- Deployment date
- 1 April 2023
- Sites
- 4
Regulatory & governance
- EU AI Act risk tier
- Limited risk
- High-risk basis
- Not applicable
- Medical device
- No
- EU MDR class
- Not a device
- CE marking
- Not required
- FDA status
- Not applicable
- ISO 14971 risk class
- Low
- GDPR processing basis
- Consent
- GDPR DPIA
- Completed
- Data identifiability
- Pseudonymised
- Explainability method
- None
- Human oversight model
- A clinician reviews every referral before assessment; risk responses trigger immediate human escalation.
NICE evidence standards
- ESF tier
- Tier B — inform / monitor
- Evidence category
- Category 2
Performance summary
- Headline metric
- Accuracy
- Value
- 0.93
- Subgroup performance assessed
- Yes
- Known bias signals
- —
Similar deployments
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Assurance Pack
Validation artefact produced by the AIH Lab review panel.
- Criteria version
- 2026.1
- Result
- PASSED
- Issued
- 15 March 2023
- Panel chair
- —
Evidence records
Studies and evaluations attached to this use case.
Prospective observational
Accuracy: 0.93
Population: IAPT self-referrals, 30k referrals
Contributors
- Deploying organisation
- [demo] Oxford University Hospitals NHS FT · Hospital / health system · United Kingdom
- AI vendor
- [demo] Limbic · United Kingdom
- Product name
- Limbic Access