When operating room scheduling data becomes trustworthy, everything changes: OR capacity optimization, block utilization improvement, surgeon access, and staff predictability. At this year’s OR Manager Conference in Anaheim, three perioperative leaders hosted the panel discussion Training AI to Optimize Block Scheduling about how they’ve used artificial intelligence to transform their OR efficiency and heighten their surgical teams’ success — not by replacing human decision-making, but by making it sharper, faster, and fairer.
Beth Orr, DNP, RN, CNOR, CSSM, NEA-BC, a Perioperative Consultant at UC Davis Health (and former Director of Ambulatory Surgery at Houston Methodist), Kate Ulrich, MS, BSN, RN, NEA-BC, Senior Vice President of Perioperative Services at Tampa General Hospital, and Yessenia Salgado, DNP, RN, NE-BC, Senior Director of Clinical Operations for Surgical Services at Tampa General Hospital shared their implementation strategies, ROI metrics, and change management lessons that turned skeptics into advocates of Apella’s OR optimization platform — a system they simply call ambient intelligence.
Their insights reveal how a combination of trust, data integrity, and continuous learning can reshape how hospitals think about surgical block scheduling, coordination between perioperative teams and physicians, insights into their results and opportunities, and beyond:
- Why manual EHR timestamps limit scheduling accuracy (and why that's not on nurses)
- How to address "big brother" concerns and build trust in ambient intelligence
- The metrics that convinced surgeons and C-suite to scale
- How to expand OR capacity without adding rooms or extending hours
- Why block scheduling optimization is about safety, not just efficiency
And they drive the discussion with results from Tampa General and Houston Methodist’s experience with Apella:
- 56 additional block hours per OR per month
- 24% improvement in OR scheduling accuracy
- 69 minutes cut from average surgical delays
- 40,000 minutes of preventable door openings eliminated
- Zero additional capital expenditure, rooms, or staff required
The problem of manual EHR data in block scheduling
Every OR professional knows the old refrain: first-case on-time starts and shorter turnover times über alles. As Kate Ulrich from Tampa General put it, “Every organization I’ve worked in, it’s the same thing. We keep asking what we can do better, but we’ve never [previously] been able to see what’s actually happening in the room.” That lack of visibility limits hospitals’ ability to optimize scheduling and stems from a fundamental problem: OR data depends on manual data entry into the EHR, usually by a circulating nurse, whose primary focus is patient care, not documentation.
Beth Orr, currently of UC Davis Health and previously of Houston Methodist, explained, “Our circulators were 98% accurate documenting when patients went in the room, but only 59% accurate for out-of-room time. Over three months, that was 500 minutes of missing data — and it wasn’t their fault. They were focused on patient care.”
Yessenia Salgado from Tampa General succinctly summarized the problem of relying exclusively on data manually entered into the EHR: “Garbage in, garbage out.” Even the most sophisticated algorithms can’t produce trustworthy predictions if they’re fed by inaccurate, delayed, or incomplete data from the EHR alone. And when clinicians lose faith in the data, the entire system breaks down — surgeon block disputes escalate, scheduling decisions feel increasingly political vs. data-driven, and capacity optimization feels impossible.
Ambient intelligence, from data insight to data impact
To address those gaps, the panelists’ teams turned to Apella's ambient intelligence—an OR management platform that uses four cameras per operating room to captures real-time activity using computer vision and machine learning. Unlike traditional OR management systems that rely on manual EHR entry alone, Apella's ambient intelligence uses:
- Four ceiling-mounted cameras per OR (set up to avoid patient identification and sterile fields)
- Computer vision that automatically identifies 50+ perioperative events
- Real-time Epic integration that writes up to 14 events directly to OpTime as they occur
- Predictive analytics that forecast case times and resource needs
“It’s not about replacing people,” Yessenia Salgado said. “It’s about helping them. When a charge nurse can see in real time where help is needed, [they don't] have to walk from room to room. [They already know] where to go.”
Kate Ulrich described the breakthrough as finally being able to see what teams had only guessed for years. “The ambient technology lets us see the real story behind the numbers — who’s doing what, when, and why — so we can fix problems that used to be invisible.”
Scheduling accuracy and trust
When the data became trustworthy, the outcomes were immediate and measurable. Beth Orr candidly recalled a case where ambient intelligence overturned a scheduling decision: “A surgeon wanted to add two cases that, according to the EHR, would go past 11pm. But the AI predicted we’d be done by 5pm. We trusted the data — and that surgeon rolled out at 4:57.”
The panel shared that, across institutions, Apella has driven consistent and transformative gains: 24% improvement in scheduling accuracy, 69-minute average reduction in surgical delays, 56 additional block hours per OR per month.
But the panelists were quick to emphasize that these metrics only tell part of the story. The real transformation came from how people responded once they could see — and trust — what was happening. “Surgeons used to say, ‘I don’t believe your data,’” Kate Ulrich laughed. “Now we can show them objective, unbiased information — and it changes the conversation.”
That shift from political negotiations to data-driven decisions reduces friction and improves relationships between perioperative leadership and surgical staff. For surgeons, this transparency builds trust. For administrators, it provides objective grounds for difficult conversations. For patients, it means quicker access to higher quality and safer care, and that can mean lives saved.
Financial impact and equity
Perhaps the most profound change came in how hospitals think about block ownership. Ambient intelligence revealed not just inefficiencies, but inequities — surgeons losing credit for shared cases, or specialists under- or overallocated based on incomplete data.
"Now we can reallocate based on reality, not perception," Kate Ulrich said of Tampa General's experience. "When we looked at neurosurgery, we realized our surgeons needed 32 more hours on Mondays—something traditional block metrics never showed us." This represented new capacity for additional cases that was previously going unused — all without needing to open more rooms or hire additional staff.
The data also supported creative new models, like virtual blocks that used predictive scheduling to open up unused time. Beth Orr recounted, “Over three months, [Houston Methodist’s] pilot generated $2.2 million in additional revenue and provided access for patients who would have otherwise waited [for months to even be seen].”
Safety and efficiency gains
By connecting continuous observations with predictive analytics, ambient intelligence helps anticipate — and prevent — the cascade of delays that often define surgical days.
Patient safety. “We reduced [the impact of] door openings by 40,000 minutes,” Kate Ulrich of Tampa General explained. “Every time that door opens, airflow changes. So, yes, it’s efficiency. But it’s also safety.”
Schedule predictability. At Tampa General Hospital, where roughly 20% of cases are unplanned add-ons, that foresight has changed how charge nurses distribute cases and manage staff. “They can look at the live dashboard, see that Room 12 will finish at 1pm, and plan accordingly. It gives them control. And it helps our teams go home on time,” Kate Ulrich said.
Automated coordination. Even communication improved. Early pilot programs introduced text notifications that automatically alert surgeons when their patients are wheels-out or the next room is ready. “One surgeon got 388 text messages in a month and said it was the best thing ever,” Kate Ulrich said, as both Beth Orr and Yessenia Salgado looked on with knowing grins and head nods. “That’s 388 phone calls we didn’t have to make.”
Staff wellbeing and retention
The predictability ambient intelligence provides directly impacts staff wellbeing and retention — a critical concern given the ongoing perioperative nurse shortage. “When teams know what’s coming, they’re less stressed. We’re not calling people at 2:30pm asking them to stay late because we can see it coming three days out,” Beth Orr added.
As the technology matures, its influence extends beyond the OR schedule. Pre-op nurses now use predictive dashboards to manage patient expectations in real time, and PACU nurses can anticipate when surges of postoperative patients are about to arrive. “We’ve gone from reactive to proactive,” Beth Orr said. “It’s like having a live weather radar for your surgical day.”
The human elements of ambient intelligence in the OR
For Tampa General Hospital and Houston Methodist, the success of ambient intelligence in the operating room is as much about ensuring trust, privacy, and governance as it is about driving measurable ROI. Clear policy and transparent communication accelerate adoption and de-risk the rollout.
Introducing new technology into an environment as vital and complex as the operating room isn’t just a technical challenge — it’s an exercise in planning and change management. “My first day at Tampa General was the governance meeting about bringing cameras into the OR,” Kate Ulrich recalled. “People were worried. They said, ‘Big Brother is watching.’ But none of us have time to watch people all day — that’s not the point.” To build confidence, the Tampa General team:
- Held town hall meetings for all OR staff
- Distributed detailed FAQs addressing concerns
- Brought compliance, legal, and risk management leaders into the process early
- Made an explicit commitment that data would never be used punitively
- Positioned cameras to ensure sterile field visibility while avoiding patient identification
“Now, they forget the cameras are even there,” Kate Ulrich said. “In fact, the rooms that don’t have it are the ones asking when they’ll get it.” That transparency of real-time data fostered a new sense of ownership among staff and physicians. Yessenia Salgado described how her teams began to see the dashboards as tools for empowerment, not surveillance: “It’s an amazing feeling when your team starts to ask, ‘What can I do to help the next case move faster?’ instead of, ‘Why is this taking so long?’”
For OR leaders planning their own implementations, the panelists recommended downloading The Complete AI Implementation Checklist for Operating Rooms — a planning resource covering infrastructure, IT needs, and systems integration requirements of deploying artificial intelligence in the OR.
The broader lesson: OR efficiency enables care quality
By the panel’s end, the conversation had moved far beyond algorithms and schedule optimization. The takeaway wasn’t just that AI can optimize OR capacity. Yes, ambient intelligence has been a key to scheduling optimization for several of the busiest and most innovative health systems in the world. But, also, good data restores trust, equity, and balance in a complex system, freeing the entire surgical team to collaborate and problem-solve for much greater impact.
“Efficiency is really safety,” Beth Orr emphasized. “We need [to always think about care in all its forms]. We can give our teams a predictable day to avoid burnout. And that’s [not only] for the nurses, the techs, the surgeons, the anesthesiologists, and the proceduralists.” It’s also for patients to be sure they’re always receiving the highest quality and safest care when they need it most. “When we can place [the true maximum] of cases in the appropriate rooms, we are able to both center on patients and [still be confident we’ll always] go home on time.”
When surgical teams can trust their data — and each other — everyone benefits: patients get faster care, staff find more predictability, and hospitals gain the capacity to sustain it all.
Check out our Complete AI Implementation Checklist for ORs to plan and track the critical success factors at every stage of deployment.