Context
Evaluations
SingleAxis evaluates how healthcare AI performs across the work it is expected to complete, the people who oversee it, and the conditions where it operates.
Evaluate the workflow.Not just the answer.
01Context
02Decision
03Action
04Oversight
05Monitoring
Workflow-level evaluation
Evaluation follows the work from input to outcome.
A benchmark score can describe a model capability. A workflow evaluation examines whether the complete system behaves correctly in the setting where people will rely on it.
Decisions
What must it determine?
Expected decisions, uncertainty, omissions, and the consequences of an incorrect conclusion.Actions
What can it do?
Tool use, permissions, downstream changes, and recovery when an action cannot be completed.Oversight
Where must a person intervene?
Approval points, escalation conditions, and the evidence a reviewer needs to make a decision.Monitoring
What changes after deployment?
Shifts in cases, users, integrations, and system versions that can introduce regression.Healthcare
Healthcare evaluation areas.
These areas organize the clinical and operational workflows SingleAxis is mapping for evaluation. They do not represent completed public suites or benchmark results.
Evaluation assets will be marked as available only when ready for external use.Evaluation area
Clinical documentation
Information capture, transformation, review, and use of clinical records.Evaluation area
Medication workflows
Medication-related context, decisions, actions, and escalation points.Evaluation area
Discharge
Information and decisions involved in transitions from care.Evaluation area
Prior authorization
Evidence gathering, criteria review, submission, and follow-up.Evaluation area
Patient communication
Messages, instructions, uncertainty, and appropriate escalation.Evaluation area
Care navigation
Routing, access, handoffs, and next-step recommendations.Evaluation area
Coding
Clinical context, code selection, supporting evidence, and review.Evaluation area
Clinical decision support
Recommendations, supporting context, uncertainty, and oversight.Evaluation area
Clinical agents
Multi-step workflows involving decisions, tools, and human control.Evaluation development
From workflow map to regression test.
The evaluation is built around the work, the system release, and the deployment decision it needs to support.
Map the workflow
Document the task, participants, systems, decisions, and handoffs.
Define expected behavior
Set permitted actions, escalation rules, and conditions that require review.
Build evaluation cases
Create representative, difficult, and long-tail cases grounded in the workflow.
Test the system in context
Evaluate the model, tools, integrations, and human interaction together.
Review the evidence
Assess findings against the agreed rubric and document limitations.
Monitor and retest
Use changes and confirmed incidents to determine what enters regression testing.
Evaluation evidence
Evidence for deployment review.
Findings are only useful when reviewers can see what was evaluated, under which conditions, and where the conclusion stops.
Evaluation record
01System and release evaluated
02Workflow and operating conditions
03Cases and scoring criteria
04Findings and supporting evidence
05Human review and adjudication
06Limitations and retest conditions
For healthcare organizations
Evaluate a healthcare AI workflow.
Tell us what system is being considered, where it will operate, and what decision the evaluation needs to support.