Autonomous Coding
Autonomous inpatient medical coding for health system revenue cycle teams
- Tool type
- Autonomous AI inpatient coding
- Made for
- Health system coding and revenue cycle teams
- Runs on
- Deployment agreed with AKASA
- Works alongside existing EHR and billing workflows; rollout is customized with AKASA.
What it does
AKASA's Autonomous Coding reads the complete inpatient chart for an encounter, including discharge summaries, operative notes, progress notes, consults, labs, imaging, and medications from all specialties. It produces a code set covering procedures, principal diagnosis, MS-DRG, present-on-admission indicators, and quality capture, with each code linked to the chart language that supports it along with its rationale and confidence level.
Health systems use it to code encounters at discharge rather than waiting days for a coder to begin work. AKASA says this can shorten discharged-not-final-coded time and accounts receivable days. Users set thresholds, service line rules, payer mix, and audit sampling, and the system codes only the categories they have approved, using ICD-10-CM/PCS and a model tuned to the health system's documentation patterns.
Designed for inpatient coding managers and revenue cycle executives at health systems with substantial inpatient volume. Access is through a demo request rather than self-serve sign-up. Outpatient encounters are planned for later, and AKASA's accuracy results come from its own blinded third-party evaluation.
What it can do
- Reads the complete inpatient chart across all specialties and document types
- Assigns procedure codes, principal diagnosis, MS-DRG, and present-on-admission indicators
- Links every code to supporting chart language with rationale and confidence
- Codes encounters at discharge rather than in a later queue
- Configurable thresholds, service line rules, payer mix, and audit sampling
- Codes only the categories the health system has approved
Example workflows
- Discharge-to-coded encounter
- Input: a discharged inpatient chart with provider notes, labs, imaging, and medications. Steps: the system reads the full chart, assigns codes, and links each code to supporting documentation. Output: a coded encounter with procedures, principal diagnosis, MS-DRG, present-on-admission indicators, and evidence for review.
- Configured review boundary
- Input: thresholds, service line rules, payer mix, and audit sampling settings. Steps: the system codes encounters within the approved boundaries and routes the rest as configured. Output: a code set limited to approved categories with documented rationale.
Before you choose
- Specific EHR and billing integrations are not named publicly; confirm supported systems during the demo.
- Outpatient facility encounters are planned for later, so current scope is inpatient.
- Accuracy results come from a vendor-commissioned third-party evaluation; validate performance on your own encounters.
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Get started
The consultation includes a live walkthrough on encounters similar to your case mix.
- Request a demo to review your case mix and coding metrics.
- Work with AKASA to configure thresholds, service line rules, payer mix, and audit sampling.
- Deploy alongside existing EHR and billing workflows, with a rollout scaled to your volume.
Plans and prices
No pricing or billing model was confirmed in the supplied sources.
We couldn’t find published prices for Autonomous Coding. 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.
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Last checked 29 Oct 2026. Every field keeps its source and date; unknown means we couldn’t confirm it.