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LibraryFamily 13 · Patient Engagement & Communication

Symptom assessment for pre-admission triage

CuratedPilotNo evidence on file

Reviewed for completeness and published to the Library.

Guides patients through a structured symptom interview and recommends an appropriate level of care, signposting to the right service.

Plain-language summary

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Clinical context
Clinical problem
Support communication
Point of care
Pre-admission
Nature of AI output
A recommendation
Clinical specialty
General practice
Care setting
Community care
Patient population
Adults using a patient-facing app to describe symptoms before contacting outpatient services.
Intended use
Guides patients through a structured symptom interview and recommends an appropriate level of care, signposting to the right service.
Technology
AI technique
NLP / large language model, Rule-based
Input data
Patient-reported data
Output type
Recommendation
Autonomy level
Informs a human (advisory)
Model provenance
Vendor proprietary
Model version
Built on a general-purpose model
Yes
Deployment
Status
Pilot
Country
Germany
Deployment date
20 May 2024
Sites
1
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
Anonymised
Explainability method
None
Human oversight model
Advisory only; patients are clearly told they are interacting with AI and urgent presentations are escalated to human triage.
NICE evidence standards
ESF tier
Tier B — inform / monitor
Evidence category
Performance summary
Headline metric
Accuracy
Value
0.71
Subgroup performance assessed
No
Known bias signals

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Contributors

Deploying organisation
[demo] Charité – Universitätsmedizin Berlin · Hospital / health system · Germany
AI vendor
[demo] Ada Health · Germany
Product name
Ada