Clinical AI Performance Assessment
Measure the real clinical impact of your deployed AI tools. We assess concordance rates, time-to-diagnosis improvements, and workflow efficiency to give you an evidence-based view of AI performance in practice.
Who is this for?
Hospitals with AI Deployed
You have AI tools live in clinical workflows and need objective measurement of their real-world clinical impact and performance.
Clinical Leadership Teams
You need structured evidence on AI performance to inform decisions about scaling, adjusting, or discontinuing AI initiatives.
IT Teams Managing AI
You are responsible for maintaining and optimising AI integrations and need measurable benchmarks to guide technical improvements.
Radiology Departments
You want to understand how AI-assisted reporting compares against radiologist-only workflows in accuracy, speed, and consistency.
Our process
Baseline Measurement
We establish current-state clinical metrics including reporting turnaround times, concordance baselines, and workflow throughput before structured AI assessment begins.
Data Collection
Systematic collection of clinical performance data across defined evaluation periods, capturing AI concordance rates, flagging accuracy, and clinician interaction patterns.
Impact Analysis
Quantitative analysis comparing AI-assisted workflows against baseline metrics, measuring time-to-diagnosis changes, concordance rates, and operational efficiency gains.
Reporting & Recommendations
Delivery of a comprehensive clinical performance report with evidence-based recommendations on optimisation, scaling, or workflow redesign.
What you receive
Clinical Performance Report
Comprehensive assessment of AI clinical impact with methodology, findings, and executive summary suitable for board-level reporting.
Concordance Analysis
Detailed comparison of AI outputs against clinical ground truth, including sensitivity, specificity, and concordance rate breakdowns by pathology type.
Workflow Impact Metrics
Quantified measurements of time-to-diagnosis, reporting turnaround, case throughput, and clinician interaction time with AI tools.
Decision Recommendations
Clear, evidence-based recommendations on whether to scale, optimise, or reconfigure AI deployment based on measured clinical outcomes.
Common questions
How long does a clinical AI performance assessment take?
A typical assessment runs over 4 to 12 weeks depending on the volume of cases and the number of AI tools being evaluated. We work with your team to define an evaluation period that provides statistically meaningful results without disrupting clinical operations.
Do we need to change our clinical workflows during the assessment?
No. Our assessment is designed to measure AI performance within your existing workflows. We observe and collect data without requiring changes to how your clinicians currently work, ensuring results reflect real-world conditions.
What types of AI tools can you assess?
We assess any AI tool deployed in clinical imaging workflows, including triage and prioritisation tools, automated detection and measurement systems, and AI-assisted reporting solutions. The methodology adapts to the specific tool and clinical context.
How is this different from the vendor's own performance claims?
Vendor performance data is typically derived from curated datasets under controlled conditions. Our assessment measures real-world clinical performance in your specific environment, patient population, and workflow context, giving you independent, unbiased evidence.
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Let's find out what your AI is really doing
Whether you need a full evaluation, a vendor readiness check, or just want to explore your options, we'll start with a conversation, not a sales pitch.
Send us a message
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