Healthcare AI governance for health system COOs
The problem from this chair
The board asked what your AI governance looks like, the answer has to survive a follow-up question, and the people who would build it are the same people running the operation.
The metrics you are actually measured on
- Third-next-available across the ambulatory footprint
- Length of stay and discharge-before-noon
- Agency and premium labour as a share of worked hours
- Denial rate and days in AR
- Provider time-to-start from signed offer
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 readiness score, then the crosswalk. You need to know which of the five areas is weakest before you spend anyone’s time, and the answer is rarely the one the executive team assumes.
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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