Technical and clinical evaluators who want the sequence, not the promise
Healthcare AI, step by step
343 of the platform's documented capabilities are AI-augmented. Each one has an input taken from the record, a check, and an output a person can accept, correct or reject.
The four steps
- 01
Scope
The layer sees the encounter and the history relevant to it — not the whole database.
- 02
Task
One task per step: structure a note, propose codes, draft a message, prioritise a queue.
- 03
Check
Deterministic rules run on the output; failures are shown, not smoothed over.
- 04
Decision
A named person accepts, edits or rejects. Only then is it part of the record.
The six questions
- What is it?
- A pipeline: retrieve the relevant part of the record, run the task, check the output against rules, present it for a decision.
- Who is it for?
- Clinical leads validating behaviour, and technical evaluators reviewing the design.
- Which problem does it solve?
- AI features are usually described by their output, so nobody can tell what was used to produce it or what would have stopped it.
- How does it work?
- Retrieval is scoped to the record in context. The task runs against that scope only. Rule checks look for missing measures, contradictions and out-of-range values. The result is shown with its sources.
- How is it different?
- The check step is part of the pipeline, not a disclaimer: a failed check surfaces as a blocking flag on the draft.
- What is the proof?
- Each generated element can be expanded to the record entries it came from.
This page is part of a platform of 2,156 clinical and operational capabilities across 8 business domains.
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343 of the platform's documented capabilities are AI-augmented. Each one has an input taken from the record, a check, and an output a person can accept, correct or reject.