The right AI can transform documentation workflows without compromising clinical nuance or compliance.

Why Pulmonology Documentation Is Complex
Pulmonology sits at the intersection of primary care, critical care, and diagnostics. Providers manage COPD, asthma, sleep apnea, pulmonary fibrosis, and more—often coordinating with multiple specialists and high patient volumes. This creates:

• Heavy documentation loads from frequent follow-ups and comorbidities
• Specialized terminology that generic AI tools miss
• Time-sensitive referrals and reports (e.g., to sleep labs or oxygen vendors)
• Custom note structures within EHRs like Epic or Athena

AI must go beyond summarization—it must understand pulmonology, integrate with EHR templates, and manage chronic disease staging, ventilator data, and longitudinal care plans.

How to Evaluate Documentation-Focused AI
Six key factors matter most:

1. Specialty Context Awareness – Trained on pulmonology-specific faxes, referrals, and device data
2. EHR-Native Execution – Writes directly into structured fields and free text areas
3. Adaptive to Templates – Follows your clinic’s note preferences
4. Agentic Completion – Pre-fills notes, updates care plans, inserts problem lists
5. Audit Trails & Compliance – Ensures all actions are reviewable
6. Workload Reduction Metrics – Demonstrates measurable time savings

Without these, AI becomes another inbox to check—not a productivity engine.

Why Honey Health Is Purpose-Built for Pulmonology
Honey Health’s AI co-workers are trained on real pulmonology workflows: pre-charting, fax parsing, referral triage, and PFT interpretation support. Unlike generic scribe tools, Honey works inside your EHR—no toggling, no new interfaces.

Key features include:

• Agent-based pre-charting with structured and unstructured note support
• Automated documentation for refills and orders (inhalers, CPAP supplies)
• Device data extraction from faxes (e.g., nocturnal oximetry, BiPAP logs)
• Care plan summarization and tagging for chronic lung disease

Clinics report faster documentation, improved billing alignment, and less after-hours charting.

Honey Health vs. AI Scribes

• Specialty training: Honey yes, scribes no
• Agentic execution: Honey yes, scribes suggest only
• EHR-native: Honey yes, scribes often external
• Multi-agent support: Honey yes, scribes no
• Custom templates: Honey yes, scribes limited
• Refill/order handling: Honey yes, scribes no

Conclusion: AI That Understands Respiratory Care
For pulmonology groups, ambient listening or dictation cleanup isn’t enough. AI must actively complete work in the background—based on deep knowledge of your specialty and EHR.

Honey Health delivers AI co-workers that adapt to your charting needs, save hours daily, and reduce documentation friction. Pulmonology teams ready to cut charting time, improve accuracy, and grow panel size without burnout should look to Honey.

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