CHAI¶
The Coalition for Health AI (CHAI) is a US non-profit whose members include health systems, technology vendors, academic centers, and patient advocates. Its published material is the basis of the lifecycle this tool tracks.
What is CHAI's, and what is ours
The six-stage lifecycle and the five principles are modeled on CHAI's published lifecycle approach; we could not retrieve CHAI's Assurance Standards Guide to check them against it. The checkpoint placement (after stages 1, 4, 5 and 6) and the A-to-D questions are this project's rendering of CHAI's go/no-go decision points. The 41 checklist criteria in this tool are original summaries written for this project — they are not the text of CHAI's Responsible AI Checklist.
CHAI's responsible-ai-content repository is published under CC BY 4.0 and may be quoted with attribution. See Notice & license.
Purpose¶
CHAI's framing is that assurance is a lifecycle property, not a gate you pass once. A model that was validated at purchase can drift, meet a different patient mix than it was built for, or be used for something nobody intended. So the material is organized around stages of a solution's life, and the same five principles are asked at every stage.
Where OPTICA asks should this organization adopt this solution, CHAI asks is this solution being developed, deployed, and operated responsibly, continuously.
The five principles¶
Every criterion in this tool is tagged with one:
| Tag | Principle |
|---|---|
| U | Usefulness, usability & efficacy |
| F | Fairness |
| S | Safety & reliability |
| T | Transparency & accountability |
| P | Security & privacy |
The tool scores each principle separately, so a solution that is performing well but has no monitoring owner shows a weak S score rather than a vaguely diminished overall one.
The six stages¶
| Stage | Name | What it establishes |
|---|---|---|
| 1 | Define the problem & plan | A real problem, the right tool for it, and a named accountable owner |
| 2 | Design the AI system | Where it sits in the workflow, who uses it, what happens when it is wrong |
| 3 | Engineer the AI solution | Traceable data and documented choices the assessment stage can verify |
| 4 | Assess | Local validation before any patient is exposed |
| 5 | Pilot | A small, time-boxed trial with stop rules |
| 6 | Deploy & monitor | Scale-up with drift monitoring, change control, and retirement criteria |
The four checkpoints¶
Stages are separated by explicit go/no-go decisions, each recorded with a rationale and a sign-off.
| Checkpoint | After stage | Question |
|---|---|---|
| A | 1 | Approve moving to design? |
| B | 4 | Approve a pilot? |
| C | 5 | Approve deployment at scale? |
| D | 6 | Periodic review — continue, change, retrain, or retire? |
Checkpoint D is the one that recurs. Each review sets the next review date, which is what drives the Needs update and Out of compliance states on the dashboard.
Applied Model Card¶
CHAI publishes an Applied Model Card template — a structured description of a solution covering basic information, uses and directions, warnings, "trust ingredients", and resources. This tool reproduces its section and field names and fills them from checklist evidence.
CHAI's files do not state one license for the model card
As checked on 2026-10-12, the v0.1 documentation PDF links CC BY-ND 4.0
(Attribution, No Derivatives), CHAI's mc-schema repository carries a
different, permissive license that allows modification, and CHAI's registry
page says "All rights reserved". A standalone template PDF was reported to
carry CC BY-NC-ND 4.0, but it is no longer online and we could not confirm
it. We have not resolved which governs, so this page makes no statement
about commercial use.
This tool uses the template's section and field names to structure its own output; it does not redistribute CHAI's document. Before you distribute a modified model card or something closer to the template, confirm the terms with CHAI or your counsel.
Testing & Evaluation Frameworks¶
Separately from the lifecycle, CHAI publishes consensus Testing and Evaluation (T&E) Frameworks per use case. These are not questions — they are recommended methods and metrics, each with an intended use, a rationale, a reference, and fields for monitoring cadence and responsible party.
Ten use cases are published on CHAI's content hub, rai-content.chai.org:
| Use case | T&E framework |
|---|---|
| Ambient AI | framework |
| Agentic AI | framework |
| Clinical decision support | framework |
| Clinical trials | framework |
| EHR information retrieval | framework |
| General health advice chatbot | framework |
| Mental health | framework |
| Patient discharge summarization | framework |
| Prior authorization criteria matching | framework |
| Sepsis risk prediction | framework |
Each is split pre-deployment and post-deployment, and within each, by the five principles.
Use these to fill the metrics table, not the checklist
A T&E framework is guidance for completing the Applied Model Card, not a third set of questions. Each entry names a method or metric with an intended use, a rationale, a reference, and fields for monitoring cadence and responsible party — which is exactly the shape of the key metrics this tool records at stage 4. See the crosswalk.
Source¶
- CHAI
- responsible-ai-content — CC BY 4.0, © 2025 Coalition for Health AI, Inc.