Assess whether to stop a model that increases alert volume without outcomes

SITUATION Unit-level complication variation table arrived with an AI tool suggesting codes the attending will not attest for quality-improvement physician. That is a Healthcare Outcomes Review decision on to stop a model in a unit with a new early-warning model.

DECISION Quality-improvement physician in a unit with a new early-warning model must choose Proceed under protocol / Pause the pathway / Escalate safety review / Hold using unit-level complication variation table after an AI tool suggesting codes the attending will not attest.

HYPOTHESES TO TEST 1. An AI tool suggesting codes the attending will not attest is noise around an already-controlled Outcomes Review process in a unit with a new early-warning model, given unit-level complication variation table. 2. An AI tool suggesting codes the attending will not attest is the event in unit-level complication variation table that forces Proceed under protocol for quality-improvement physician under Healthcare. 3. Unit-level complication variation table shows a one-file miss after an AI tool suggesting codes the attending will not attest, not a Outcomes Review program failure. 4. Unit-level complication variation table cannot decide to stop a model yet after an AI tool suggesting codes the attending will not attest; hold is the only Healthcare close a unit with a new early-warning model can defend.

ANALYSIS REQUIRED 1. Trace access logs and outputs to the rule quality-improvement physician must apply. 2. Assess patient-safety and HIPAA / minimum-necessary implications of to stop a model. 3. Quantify who is harmed if unit-level complication variation table is wrong. 4. For this Healthcare Outcomes Review file, read unit-level complication variation table against an AI tool suggesting codes the attending will not attest and write the one fact that would move to stop a model for quality-improvement physician.

RECOMMENDATION Choose Proceed under protocol / Pause the pathway / Escalate safety review / Hold on this Healthcare / Outcomes Review packet (unit-level complication variation table after an AI tool suggesting codes the attending will not attest). Lead with the Healthcare option unit-level complication variation table can support after an AI tool suggesting codes the attending will not attest, then the two facts that force it, then the Monday action for quality-improvement physician in a unit with a new early-warning model.

COMMAND RETURNS - Bottom-line Healthcare option on to stop a model, then the evidence in unit-level complication variation table, then the action for quality-improvement physician - Hypothesis scorecard against unit-level complication variation table: supported / rejected / untestable - Outcomes Review finding in unit-level complication variation table that a second reviewer can re-perform - Missing page in unit-level complication variation table after an AI tool suggesting codes the attending will not attest, if any