Clinical Documentation Assistant
Clinical note automation from doctor-patient conversations with terminology-aware structure.
Why clinical documentation burdens care teams
- ●Clinicians spend substantial time converting conversations into structured notes.
- ●Documentation quality varies across providers and specialties.
- ●Medical terminology and coding accuracy are difficult to maintain manually.
- ●Administrative overhead reduces direct time available for patient care.
What Clinical Documentation Assistant provides
Conversation Transcript
Cardiology follow-up · Dr. Chen · 4 min 12 sec
Visit Info
Medical conversation transcription
Capture doctor-patient interactions into accurate transcripts.
Conversation Transcript
Cardiology follow-up · Dr. Chen · 4 min 12 sec
Visit Info
Clinical note generation
Produce structured notes from consultation context.
Structured Clinical Note
SOAP format · Auto-generated from transcript
Subjective
Patient reports mild exertional chest pressure after climbing stairs, lasting ~5 min, self-resolving with rest. No radiation, no SOB, no syncope.
Objective
BP 128/82, HR 74 regular, SpO2 98%. Cardiac auscultation: S1/S2 normal, no murmurs.
Assessment
Stable exertional angina. Well-controlled hypertension. Low acute risk.
Plan
Continue metoprolol 50mg BID. Order resting ECG. Follow-up in 2 weeks. Patient to report any worsening symptoms immediately.
Note Status
Terminology alignment
Map outputs to medical terminology and coding standards.
Medical Coding Alignment
Automated terminology mapping
Coding Suggestions
| Term | System | Code | Status |
|---|---|---|---|
| Chest pain, unspecified | ICD-10 | R07.9 | mapped |
| Electrocardiography ordered | CPT | 93000 | mapped |
| Hypertensive heart disease | SNOMED | 194767001 | mapped |
| Beta-blocker continuation | RxNorm | — | review |
Mapping
Documentation workload reduction
Cut admin time so providers can focus more on care.
Auto-Filled EHR
Documentation time reduced by 38%
EHR Field Completion
| Field | Value | Status |
|---|---|---|
| Chief Complaint | Exertional chest pressure | auto-filled |
| Vitals Summary | BP 128/82, HR 74, SpO2 98% | auto-filled |
| Assessment | Stable angina, controlled HTN | auto-filled |
| Plan | Continue metoprolol, ECG, 2-wk f/u | auto-filled |
| Medications | Metoprolol 50mg BID | auto-filled |
Time Savings
5 fields auto-populated from transcript
38%
time saved
Efficiency
Policy-bound agents
Capability enforcement ensures autonomous systems operate within explicit boundaries.
Governance Flow
Policy-bound agent execution ensures autonomous systems operate within boundaries.
Autonomous systems require explicit boundaries.
Where it sits in the stack
PlantoOS Architecture
The stack relationship between apps, agents, runtime, and systems.
Applications
Products and workflows
Agents
LLM-powered autonomous units
PlantoOS Runtime
Execution · orchestration · control
Capability Layer
Policy enforcement and tool access
Medhara Core
Memory · governance · lineage
Enterprise + Public Systems
Databases, APIs, infrastructure
A new compute layer for systems operated by agents.
Key workflows
How data flows through the system in typical usage patterns.
Workflow 1
Input
Doctor-patient interaction
Core Process
Transcribes and structures clinically relevant content
Output
Draft note with key findings and context
Workflow 2
Input
Clinical documentation review
Core Process
Aligns terminology and formatting to medical standards
Output
Consistent, compliant documentation output
Workflow 3
Input
Visit summary handoff
Core Process
Generates concise care summary for downstream teams
Output
Improved continuity across clinical workflow
Measured outcomes
↓ 25–45%
Documentation time per visit
↑ 15–30%
Note consistency
↑ 10–20%
Clinician patient-facing time
Indicative ranges from internal benchmarks and early deployments; results vary by workload, model, and infrastructure.
How it integrates
SDK-first integration — governed from the first line of code.
Connect clinical systems
Integrate transcripts and EHR workflows
Set documentation templates
Define specialty-specific note structures
Deploy in care loop
Generate notes with clinician-in-the-loop review