The Clinical Friction Ledger: Should Every Healthcare AI Tool Remove More Work Than It Creates?

The Clinical Friction Ledger: Should Every AI Feature Remove More Work Than It Creates?

One question I keep coming back to is this: How can a healthcare organization determine whether an AI tool is actually reducing work?

I propose a simple working framework—the Clinical Friction Ledger.

On one side, record the friction removed: documentation time, unnecessary clicks, repeated data entry, handoffs, and waiting.

On the other side, record the friction added: verification time, new alerts, exception handling, training, and work quietly transferred to another person or shift.

An AI model can look impressive in a demonstration while making the overall care process harder.

Before an AI pilot is scaled, both sides of this ledger should be examined. If the friction added outweighs the friction removed—or if the burden is simply shifted to someone else—the productivity claim is incomplete.

The real measure of success is not only what the AI can do. It is whether the people closest to care experience less friction because of it.

What would you put on each side of the Clinical Friction Ledger?