AI Sepsis Bundle Compliance Improvement Plan Playbook

A health system's 3-hospital network achieved 58% compliance with the SEP-1 bundle in the most recent CMS measurement period, against a national benchmark of 72%. The lowest-performing hospital (Hospital C) is at 43%. The network's VP of Quality needs an improvement plan before the next board presentation.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A health system's 3-hospital network achieved 58% compliance with the SEP-1 bundle in the most recent CMS measurement period, against a national benchmark of 72%.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Sepsis Bundle Compliance Improvement Plan".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• SEP-1 bundle compliance data by hospital, unit, and element (past 4 quarters)
• Root cause analysis summaries from the 3 lowest-compliance hospitals
• CMS SEP-1 abstraction specifications
• Best practice documentation from high-performing peer hospitals
• Current sepsis order set for each hospital

Attachments: Documents (Documents)

You are a quality improvement specialist developing a sepsis bundle compliance plan for a 3-hospital health system. I am attaching:

Work only from the attached source files. If a conclusion is not supported, say so.

Produce:
1. Identify the specific bundle elements with the lowest compliance rates: which elements (blood cultures before antibiotics, lactate, fluid resuscitation) are driving the failures?
2. For Hospital C (43%), identify whether the failure is systemic (workflow, order set design) or unit-specific (ED vs. ICU vs. floor) and what the contributing factors are.
3. Develop a prioritized improvement plan: what changes to order sets, workflows, and accountability structures will move the needle fastest.
4. Estimate the expected compliance improvement from each intervention based on evidence from peer hospitals.
5. Tell me what a 70% compliance target means for Hospital C in terms of specific number of compliant cases and what the mortality impact could be.

Call out where independent models are likely to disagree, and list follow-up documents a reviewer should request.

What to expect

• Bundle element failure analysis by hospital and unit
• Hospital C root cause analysis
• Prioritized improvement plan with evidence base
• Expected compliance improvement estimates
• Compliance target translation to cases and mortality impact

Review before you act

• Validate this output against source files before relying on it: Identify the specific bundle elements with the lowest compliance rates: which elements (blood cultures before antibiotics, lactate, fluid resuscitation) are driving the failures?.
• Validate this output against source files before relying on it: For Hospital C (43%), identify whether the failure is systemic (workflow, order set design) or unit-specific (ED vs. ICU vs. floor) and what the contributing factors are.
• Validate this output against source files before relying on it: Develop a prioritized improvement plan: what changes to order sets, workflows, and accountability structures will move the needle fastest.
• Validate this output against source files before relying on it: Estimate the expected compliance improvement from each intervention based on evidence from peer hospitals.
• Confirm every cited figure, date, counterparty, or requirement against the attached originals — models compress and can drop a qualifier.
• Treat disagreement between models as a review item, especially on classification, materiality, and recommended next action.
• Do not authorize an operational, clinical, legal, credit, or enforcement action solely because the models agree.