Analysis of 250,000+ patient encounters across 50 emergency departments finds statistically significant improvements in charge capture and patient throughput
SAN FRANCISCO, CA, UNITED STATES, June 9, 2026 /EINPresswire.com/ — Sayvant, the ambient documentation platform built by and for acute care physicians, today published findings from the largest multicenter study of AI-assisted clinical documentation in emergency medicine. The study analyzed more than 250,000 patient encounters documented with Sayvant across 50 emergency departments against a historical baseline of more than 20 million encounters spanning three years. The sites spanned academic medical centers, community hospitals, rural EDs, and freestanding facilities.
The results were statistically significant and consistent across every care setting and both clinician groups. AI-assisted documentation with Sayvant produced a 2.5% increase in professional fee charges per encounter for physicians and 3.7% for advanced practice providers. Time-to-provider fell 5.9% for physician-led encounters and 9.5% for APP-led encounters. Admission and discharge turnaround times improved across both groups. All findings were produced by a hierarchical mixed-effects model controlling for payer mix, encounter acuity, clinician-level variance, site effects, and seasonality.
The mechanism behind the financial improvement was driven by increased defensibility of the care delivered, rather than increased visit volume per clinician. Encounters that clinically warranted a higher E/M levels and critical care were more consistently captured at the level the care actually justified. The gain is in closing the gap between the care delivered and what the note reflects.
“Emergency medicine physicians are being asked to document more thoroughly than ever, under conditions that make thoroughness nearly impossible,” said Justin Mardjuki, CEO of Sayvant. “The 2023 CMS revisions raised the bar on medical decision-making documentation at the same moment that ED volumes returned to pre-pandemic levels. This study gives the field a rigorous, multi-site answer to the question that every medical director has been asking: does AI documentation actually move the numbers that matter, or does it just move faster? Across 50 departments and 250,000 encounters, it moves charges up and wait times down.”
Earlier studies of ambient documentation tools reported promising reductions in charting time but were limited to single sites and focused narrowly on time savings. This study is the first to measure patient throughput and professional fee capture as primary outcomes at a scale large enough to control for the confounders that drive real variation in emergency medicine revenue: payer mix, acuity, seasonality, and the billing differences between physicians and APPs.
“The documentation problem in emergency medicine is not a software problem. It is a clinical reasoning problem,” said Andrew Napier, MD FAAEM, Co-Founder and Head of Clinical AI at Sayvant. “An ED note is a structured argument for medical necessity. Most ambient tools capture what was said. Sayvant generates what the note needs to reflect. That is why these results look different from what earlier studies found.”
The full research report is available at https://sayvant.com/roi-of-ai-documentation.
About Sayvant
Sayvant is the ambient documentation platform built by acute care physicians. It generates defensible notes and delivers real-time clinical and quality safeguards, helping clinicians spend less time documenting and more time focused on patient care. Health systems and physician groups use Sayvant to strengthen documentation integrity, improve charge capture, and support more consistent, high-quality care. Learn more at Sayvant.com.
Naor Chazan
Healthcare AI Automation Inc. dba Sayvant
naor.chazan@sayvant.com
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