Healthcare AI governance for CMIOs and clinical informatics leaders
The problem from this chair
You are accountable for tools you did not procure, embedded in products you did not choose, and the governance framework everyone cites stops exactly where your job starts.
The metrics you are actually measured on
- Documentation time per encounter and after-hours EHR time
- Alert burden and override rate
- Model performance by subgroup on your own population
- Time from validation request to result
- Inbox volume per provider
Every framework in the library is anchored to metrics like these rather than to model performance, because model performance is not what you are asked about in a board meeting.
Where to start
The evidence library, starting with the local validation memo. It is the artifact that most often does not exist and the one that most often should.
The honest limit
Nothing here removes the need for judgment about your own organisation. The instruments make the judgment faster and make it auditable. They do not make it for you.
Written and reviewed by Neel Chauhan, MD MBA, physician-executive and founder of the Healthcare AI Institute. Last reviewed 2026-07-30.
Written per role rather than templated: the pain, the metrics and the first artifact genuinely differ by seat, which is what makes these distinct pages rather than one page repeated.
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