CDI Optimizer

What it does

AKASA CDI Optimizer takes inpatient encounter records from a health system, including labs, vitals, medications, and clinical documents, and reviews each inpatient encounter across service lines, both after discharge and before billing. It outputs prioritized documentation query suggestions for clinical documentation integrity (CDI) teams. Each suggestion includes a justification, exact quotes from the record, and direct links to supporting documentation.

CDI teams use it as a review queue. High-confidence, high-impact cases appear in a dashboard that can be sorted by DRG impact, quality indicators, and AI confidence level. Specialists validate each suggestion against chronological clinical evidence, then engage providers, track responses, and update cases. Embedded coding guidelines and codebooks appear alongside suggestions, and prebill review can be done with coding staff in the same platform.

The product is aimed at CDI specialists and coding teams at health systems working on documentation completeness, quality metrics, and compliance. Access begins with a request to connect with an AKASA expert. Suggestions require CDI specialist validation and provider engagement, and the tool does not autonomously code.

What it can do

• Reviews every inpatient encounter across service lines, post-discharge and prebill
• Synthesizes labs, vitals, medications, and documents to identify missed documentation opportunities
• Prioritizes cases in a dashboard by DRG impact, quality indicators, and AI confidence
• Presents clinical evidence chronologically by diagnosis and query opportunity for specialist validation
• Provides justifications, exact quotes, and direct links to supporting documentation
• Supports real-time prebill collaboration between CDI and coding staff

Example workflows

Inpatient encounter query review

Input: a completed inpatient encounter's labs, vitals, medications, and documents. Steps: the GenAI analyzes the encounter for missed documentation opportunities and ranks cases on the dashboard; a CDI specialist reviews the chronological evidence and validates or rejects each suggestion. Output: validated query suggestions with quotes and links to supporting documentation, ready for provider engagement.

Prebill documentation and coding alignment

Input: encounters pending prebill review. Steps: the GenAI surfaces documentation opportunities; CDI and coding staff review the same suggestions in the platform; approved suggestions are updated on the case. Output: a case record with agreed documentation and codes before billing.

Before you choose

• Suggestions require CDI specialist validation and provider engagement; the tool does not autonomously code or query.
• Pricing, implementation timeline, and data requirements must be confirmed directly with AKASA.

Listed under

• Healthcare
• Billing and revenue cycle
• Scribes and documentation
• Cdi
• Clinical documentation
• Compliance
• Genai
• Hospitals

Get started

A form connects visitors with an expert; no self-serve sign-up is described.

1. Contact AKASA through the CDI Optimizer page to request a consultation with an expert.
2. Provide health system data access so the GenAI can review inpatient encounters.
3. Configure dashboard prioritization preferences such as DRG impact, quality indicators, and confidence thresholds.

Pricing, trial availability, and billing model must be confirmed directly with AKASA.

We couldn’t find published prices for CDI Optimizer. See their pricing page ↗

Sources for this overview

Product pages, documentation, and pricing checked 29 Oct 2026. Each source supports part of the overview; availability and prices can change.

• AKASA CDI Optimizer ↗akasa.com

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akasa.com: product, pricing and policy pages

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knowledge_base

Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.