AI Playbook for Sepsis AI Implementation Business Case

A 450-bed community hospital is evaluating a commercial AI sepsis prediction tool costing $380,000 annually. The hospital treats 680 sepsis patients per year. Current sepsis mortality is 14.2%. The vendor claims the tool reduces sepsis mortality by 18% in clinical trials. The CMO needs a business case for the board.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A 450-bed community hospital is evaluating a commercial AI sepsis prediction tool costing $380,000 annually.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Sepsis AI Implementation Business Case".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• Vendor contract and pricing
• Vendor clinical study results (18% mortality reduction claim)
• Hospital sepsis volume and outcome data (past 12 months)
• Average revenue per sepsis case (DRG data)
• Hospital cost per sepsis death (including family notification, mortality review, regulatory impact)

Attachments: Documents (Documents)

You are a health economics specialist building a sepsis AI implementation business case for a hospital board. I am attaching:

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

Produce:
1. Assess the vendor's 18% mortality reduction claim: what is the study design, what is the confidence interval, and is it applicable to a community hospital population vs. the academic centers in the study?
2. Calculate the expected mortality impact: at 14.2% baseline mortality and 18% relative reduction, how many lives saved per year?
3. Build the financial case: total cost of ownership vs. financial benefit from reduced LOS, reduced complications, and quality metric improvement.
4. Identify the implementation risks: what workflow changes are required, what is the alert fatigue risk, and what is the integration complexity?
5. Tell me the board presentation recommendation: yes/no and why, with the specific ROI calculation and the conditions for the decision.

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

What to expect

• Vendor study generalizability assessment
• Projected mortality impact calculation
• Full financial ROI model
• Implementation risk assessment
• Board recommendation with ROI and conditions

Review before you act

• Validate this output against source files before relying on it: Assess the vendor's 18% mortality reduction claim: what is the study design, what is the confidence interval, and is it applicable to a community hospital population vs. the academic centers in the study?.
• Validate this output against source files before relying on it: Calculate the expected mortality impact: at 14.2% baseline mortality and 18% relative reduction, how many lives saved per year?.
• Validate this output against source files before relying on it: Build the financial case: total cost of ownership vs. financial benefit from reduced LOS, reduced complications, and quality metric improvement.
• Validate this output against source files before relying on it: Identify the implementation risks: what workflow changes are required, what is the alert fatigue risk, and what is the integration complexity?.
• 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.