The 70 Percent Problem: Fixing Clinical Documentation With Multi Agent AI
Healthcare providers spend as much as half of every working day on documentation instead of patients. Between typing notes, clicking through EHR fields, and finishing charts after hours, the paperwork has quietly become the job, and patient care has become the interruption.
Why this keeps costing you
Every additional minute spent charting is a minute not spent examining, diagnosing, or listening to a patient. Manual transcription is slow and error prone, specialty documentation formats (SOAP notes, OB/GYN reports, discharge summaries) each follow different structures, and most of this work still happens after the clinic has closed for the day. The result is fewer appointments per day, rushed notes that miss clinical detail, and a documentation burden that is now one of the leading drivers of physician burnout.
How we build it
We build a three agent pipeline rather than a single chatbot bolted onto the EHR. The first agent handles audio capture over a persistent WebSocket connection and runs streaming speech to text with speaker diarization, so every line is correctly attributed to physician or patient, including encounters with a family member or interpreter present. The second agent, built on GPT-4o with prompt chains tuned per note type, converts the transcript into a structured note — SOAP, OB/GYN, discharge summary, or another specialty format — and simultaneously proposes ICD-10 and CPT codes based on what was actually discussed. A third review agent cross checks the draft against the patient's existing chart before the physician sees it, surfacing inconsistencies or clinical red flags rather than letting them slip into the record. The finished note reaches the EHR through the Redox integration engine, which speaks the native API of Epic, Cerner, Athenahealth, and more than 100 other systems, so nothing is copied and pasted by hand.
What this looks like once it is running
- 1Live transcription during the visit, with speaker diarization built in
- 2Automated SOAP notes and specialty specific documentation formats
- 3ICD-10 and CPT code suggestions generated directly from the encounter
- 4Direct EHR sync with Epic, Cerner, Athenahealth, and 100+ systems through Redox
- 5Physician review and sign off in 30 to 60 seconds instead of writing from scratch
In production, this architecture has cut documentation time by 70 percent while holding transcription accuracy above 95 percent, with real time latency under 500 milliseconds. That is not an incremental improvement to a note template. It is the difference between finishing a clinic day on time and taking three hours of charting home.
For more details, click the relevant case study link below.
View Medscribe by Zaltech AI case studyMedScribe / Clinical Documentation Platform
This exact pipeline is live today as Zaltech's Clinical Documentation Platform (MedScribe). It is already handling real patient encounters in primary care, mental health, and specialty practices — not a pilot or an MVP. A physician presses record when the patient enters the room, MedScribe listens in the background and transcribes with 95%+ accuracy, and a complete SOAP note with suggested ICD-10 and CPT codes is ready within seconds of the visit ending. Review takes 30 to 60 seconds, then the note goes to the EHR with one click. The platform runs on encrypted storage with a signed BAA and full audit logging, and holds an 85% reduction in API cost alongside the 70% documentation time cut.
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Want this one built for your business?
We will walk you through the architecture, what it takes to integrate with your systems, and a realistic timeline — before anyone signs anything.