Ask any OR manager, and they’ll tell you that speedy turnovers are crucial for keeping surgeries on schedule. When turnovers run long, they disrupt the entire day’s workflow, impacting patient care, morale, and hospital costs. Despite the high stakes, many hospitals rely on various staffing methods that often fail to address the root causes of delays.
In our last post, we examined three common approaches hospitals use to improve turnover times — methods that have historically made the problem worse.
Why don’t these tactics work? They lack a foundation in data to drive and manage process improvement. Without accurate and timely data, OR teams can’t identify the source of an issue or implement meaningful changes. This is where technologies like AI can make all the difference, replacing guesswork with actionable metrics that enable surgical teams to drive real results.
Evaluating your OR turnover strategy
Improving turnover efficiency starts with collecting the right data to pinpoint delays and build workflows that address critical bottlenecks. Without more accurate and contextual data and the tools to capture it, hospitals struggle to achieve meaningful progress. After all, you can’t fix what you can’t measure.
Consider these four questions to evaluate whether your hospital is equipped to optimize turnover efficiency:
1. Are you tracking the right turnover metrics?
Many hospitals measure turnover time as a single “start-to-end” metric — the duration of the entire turnover from when the last patient was wheeled out of the OR until when the next patient is wheeled in — which provides an incomplete picture. This simplified approach overlooks the flow of staff, equipment, and tasks during turnovers. Is the delay caused by extended cleaning by the environmental services team? Idle time before staff begin setting up the operating room? Coordination delays stemming from pre-op? Something else? Without granular, context-aware data, OR managers are left guessing, relying on anecdotal evidence that rarely leads to effective solutions.
2. Can you monitor turnovers in real time?
Turnover data is often retrospective, a byproduct of documenting patient wheels-out to wheels-in. But to keep the OR running on schedule, charge nurses need to be able to monitor turnovers as they happen. Due to data latency, charge nurses are typically unable to identify issues in real time, course-correct as problems arise, or prevent cascading delays.
3. Is your data collection method accurate and unbiased?
Manual data entry introduces biases and inaccuracies, as the information reflects differing individual perceptions of turnover stages, teamwork, and timing. This can hinder OR managers’ ability to make informed decisions and can undermine staff trust in the EHR data, reducing their willingness to implement changes. Objective, automated data collection eliminates these issues, ensuring reliable metrics.
4. Is your data actionable?
In most cases, turnover metrics aren’t clearly actionable to OR managers. Ideally, OR staff should be able to predict turnover times based on case type, time of day, day of week, and other factors. Without robust historical metrics, hospitals rely on anecdotes instead of data to drive action.
Bridge the data gap with AI-powered solutions
Better data and advanced tools are essential to improving OR turnover efficiency, and AI-driven technologies are uniquely positioned to bridge this gap. Studies show that context-aware systems like AI have proven vital for enhancing efficiency in high-risk environments like ORs, where timely access to comprehensive data is critical for understanding the full picture.
Apella’s AI-powered solution delivers precisely this capability, giving OR staff an unprecedented level of real-time visibility into OR events. Using computer vision and machine learning, Apella automatically captures a detailed, context-rich timeline of turnover events — tracking key activities and objects throughout every phase of the turnover process.
Apella’s AI can detect when turnovers both begin and end, as well as each distinct phase within the turnover, such as cleanup and equipment setup. This level of context is not usually documented in the EHR without specific intervention from a circulating nurse or another member of the perioperative team (who is typically busy working with patients in pre- and post-op). By automating the capture of specific turnover milestones and granular events, OR staff can:
- Pinpoint inefficiencies: Track turnover metrics not available in the EHR to identify where true turnover processes break down.
- Reduce human error: Unburden staff from excessive documentation responsibilities, and reduce execution inefficiencies caused by multitasking and divided attention.
- Build team trust: Foster teamwork and trust by uniting staff around objective, unbiased data to identify process improvements and promote a culture of continuous improvement.
Driving turnover efficiency with Apella
1. Real-time turnover visibility for immediate action
Apella’s computer vision automatically detects events in real time, giving OR teams the level of visibility needed to anticipate and maintain a smooth, on-time schedule. Apella provides OR managers with a first-of-its-kind visualization of turnover progress, including:
- Live Gallery View of video feeds from each OR with vital real-time information on case status
- Turnover Goal-Setting that enables each site to set a unique turnover goal for benchmarking
- Color-Coded Case Status Indicators to assess each OR status live, at a glance:
- Wrap-Up (green status): case is wrapping up and will soon need staff for turnover
- Turnover In Progress (yellow status): room is in turnover and on schedule
- Turnover Running Late (red status): room is in turnover and is exceeding the organization’s specific turnover duration goal
- Turnover Stopwatch that tracks precisely how long each turnover is taking in real time, down to the second
With this live view, OR staff gain the real-time insights they need to keep turnovers — and the day’s schedule — on track. They can anticipate where environmental services staff will be needed next and allocate resources accordingly, minimizing downtime between turnovers. And when turnovers run late, they can act immediately to course-correct and prevent compounding delays in the schedule.
2. Predictive turnover forecasting
OR managers typically have little visibility into how long upcoming turnovers will take and how schedule delays throughout the day are expected to impact turnover staffing needs. Apella’s predictive turnover forecasting addresses these blind spots, providing OR staff with tools to plan, adjust, and make proactive staffing decisions in real time to prevent further delays before they occur.
How Apella’s turnover forecasting works:
- Turnover Time Predictions use historical case data to forecast future turnover durations and continuously update these predictions in real time as the day progresses and circumstances change.
- Turnover Indicators display clear visual signals (yellow or red label) within the day’s schedule, allowing staff to quickly see expected turnover times between procedures.
- Overlapping Turnover Visibility makes it easy for staff to identify when multiple turnovers are expected to occur simultaneously, allowing teams to plan and effectively allocate resources.
With Apella’s turnover forecasting, OR managers can move from reactive to proactive turnover planning. Managers can identify turnovers predicted to take longer than expected, evaluate if this aligns with the complexity of the case, and adjust staffing to minimize delays. And in scenarios where multiple turnovers are forecasted to overlap, as shown in the visual example above, teams can quickly spot the overlap and reallocate staff, as needed.
3. Turnover quality control
Effective turnover management requires a detailed understanding of what happens during each phase of the process. Apella’s advanced tools provide OR managers with the insights they need to move beyond anecdotal observations and into a data-driven approach to turnover quality control.
Apella’s unique AI computer vision automatically captures and analyzes detailed turnover event data, including:
- Insights Dashboard analyzes turnover trends over time, broken down by cleaning and setup, with flexible and granular filtering options.
- Retroactive Video Review enables OR managers to access videos to review past turnovers and visually verify what occurred during each phase.
- Detailed Turnover Event Timeline automatically detects and timestamps each stage of the turnover process, including cleanup and setup time.
- Occupancy Detection automatically tracks ongoing room occupancy throughout the turnover.
For the first time, instead of relying on high-level turnover time metrics, OR managers have deep visibility into turnover data, helping them identify patterns or outliers — like whether certain delays are tied to a specific time of day, procedure, or room. Managers can dive even deeper to view video footage of cleanup, setup, and any idle time in between. Armed with objective insights, they can identify accountable owners, determine where targeted improvements are needed, and build trust in data-driven decisions that drive meaningful results.
Take control of OR turnovers
Apella’s approach helps shift turnover improvement from a black box to a more transparent, data-driven, and outcome-oriented process.
If turnover efficiency is a key initiative for your hospital, contact us to learn how Apella can help you transform your OR.