A newly published study from Houston Methodist helps answer that question. Authored independently by researchers at the health system, led by Chief Innovation Officer and Executive Vice President Roberta Schwartz, and published in the peer-reviewed Journal of Imaging, the study found that deploying Apella in a high-acuity cardiothoracic suite was associated with a statistically significant increase in monthly surgical case volume. To our knowledge, it's the first peer-reviewed study to demonstrate an ambient AI platform increasing operating room capacity.
The numbers, up front
- 7% increase in monthly surgical case volume
- ~25 additional cases per month and ~300 additional cases per year
- All in the same rooms, with the same staff, during the same operating hours
Why case volume is the metric that matters
Nowhere is operational efficiency more consequential than in the operating room. It is one of the most complex and revenue-critical environments a hospital runs. For health systems trying to expand access and strengthen financial performance, the OR is one of the clearest places to get more value and deliver more patient benefits from the infrastructure they already have.
Perioperative AI platforms often report gains in process metrics, including turnover time, on-time starts, and late-start minutes. Those matter, but they're not what executives ultimately track. Case volume is the highest-signal indicator of whether OR capacity is actually being used well, and it directly drives patient access and revenue.
A study built to hold up to scrutiny
Most vendor evaluations rely on simple before-and-after comparisons. But hospitals are dynamic environments with staffing shifts, seasonal fluctuations, and system-wide initiatives all influencing outcomes independent of any one technology.
Houston Methodist's research team took a more rigorous approach. To evaluate Apella's impact, the team analyzed more than 120,000 surgical cases from 2024 and 2025, comparing case volume at Walter Tower — a 15-room cardiothoracic suite where Apella was deployed — against 11 other Houston Methodist sites that hadn't yet adopted the platform. Because every site sat within the same health system, region, and organizational environment, researchers could better isolate Apella's effect from other changes across the system.
Alongside the increase in case volume, researchers also observed:
- Late starts decreased by 2.7 minutes per case
- Unplanned late time and room utilization both trended favorably
- Case mix and total operative minutes stayed stable — meaning the added volume came from better use of existing capacity, not from shifting toward shorter or simpler cases
Learn how Apella is associated with measurable case volume increases across hospitals.
Read the full analysis
Proof, not just promises
This is the distinction that matters for hospital leaders evaluating ambient AI. Many AI platforms make similar claims. What's harder to find is peer-reviewed evidence tied to an outcome that hospital executives actually care about.
“Claims about AI's impact in surgery are often met with skepticism, and understandably so," said Roberta Schwartz of Houston Methodist. "That's why we approached this work with the same rigor as any clinical research study, using independent peer review and a methodology designed to demonstrate causation, not just correlation. The result is evidence we can confidently stand behind."
The reliability of Apella's underlying computer vision technology has already been independently peer-reviewed and validated. This new study extends evidence beyond technical performance, evaluating whether deployment was associated with measurable operational impact. Specifically, it found an association between use of Apella and a sustained increase in surgical case volume, enabling the health system to increase case throughput and treat more patients using the operating rooms, staff, and schedule it already had.
And the findings from Houston Methodist's Walter Tower are not an isolated result. In a separate analysis spanning multiple health systems, deploying Apella was associated with an average increase of two additional surgical cases per OR per month, expanding patient access with no additional resources or hours.
What this means for OR capacity strategy
Health systems looking to increase surgical capacity have traditionally relied on initiatives such as Lean Six Sigma, scheduling redesigns, and anesthesia workflow improvements. While these approaches can be effective, they often require significant overhead to sustain, in the form of time, staff, and money, as well as ongoing process iteration and change management.
Ambient AI offers a different approach. Rather than relying on retrospective documentation, it continuously captures what's happening in the OR. It provides real-time visibility into key milestones, including patient entry and exit, draping, turnover, and back-table readiness. That gives perioperative teams objective data they can use to coordinate care, identify bottlenecks, and make operational decisions as the day unfolds.
For hospital leaders evaluating ambient AI, independent evidence matters. This study doesn't just measure operational metrics. It evaluates whether ambient AI was associated with increased surgical case volume, one of the outcomes that matters most to health systems seeking to expand OR capacity.
Learn how Apella is associated with measurable case volume increases across hospitals.
Read the full analysis