LibraryFamily 4 · Surgical Planning & Navigation
Pre-operative risk-stratification model for major surgery
ValidatedActive deploymentRobust evidence
Formally validated with a published Assurance Pack.
Computes a 30-day mortality and morbidity risk score from pre-operative records to support anaesthetic optimisation and shared decision-making.
Plain-language summary
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Clinical context
- Clinical problem
- Predict a future risk
- Point of care
- Treatment planning
- Nature of AI output
- A risk score
- Clinical specialty
- Surgery
- Care setting
- Hospital — outpatient
- Patient population
- Adults scheduled for elective major non-cardiac surgery.
- Intended use
- Computes a 30-day mortality and morbidity risk score from pre-operative records to support anaesthetic optimisation and shared decision-making.
Technology
- AI technique
- Classical machine learning
- Input data
- Structured EHR data, Laboratory results
- Output type
- Risk score
- Autonomy level
- Informs a human (advisory)
- Model provenance
- Built in-house
- Model version
- preop-2.0
- Built on a general-purpose model
- No
Deployment
- Status
- Active deployment
- Country
- Spain
- Deployment date
- 1 September 2024
- Sites
- 2
Regulatory & governance
- EU AI Act risk tier
- High-risk
- High-risk basis
- Annex III use case
- Medical device
- No
- EU MDR class
- Not a device
- CE marking
- Not required
- FDA status
- Not applicable
- ISO 14971 risk class
- Medium
- GDPR processing basis
- Public interest
- GDPR DPIA
- Completed
- Data identifiability
- Pseudonymised
- Explainability method
- Post-hoc
- Human oversight model
- Anaesthetist reviews the risk band before booking; no autonomous decision.
NICE evidence standards
- ESF tier
- Tier C — treat / diagnose / calculate risk
- Evidence category
- Category 3
Performance summary
- Headline metric
- AUC / AUROC
- Value
- 0.85
- Subgroup performance assessed
- Yes
- Known bias signals
- Slight under-performance for patients with prior cancer; periodic recalibration scheduled.
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Evidence records
Studies and evaluations attached to this use case.
External validation
AUC / AUROC: 0.83
Population: External multi-site validation, 12k procedures
Prospective clinical trial
AUC / AUROC: 0.85
Population: Two-centre prospective surgical cohort, 5k procedures
Contributors
- Deploying organisation
- [demo] Hospital Clínic de Barcelona · Hospital / health system · Spain
- AI vendor
- —
- Product name
- —