Managing operating room capacity, without the support of analytics-based surgical scheduling software, is a constant challenge. Perioperative clinicians and staff are frustrated by the empty ORs and idle equipment that result from suboptimal scheduling processes and inadequate capacity metrics. While OR managers and schedulers work tirelessly to allocate surgeon time and make the most of the facilities available, their efforts often lead to further struggle. Typical “best practices” and measurements often fail to address the underlying causes of the problems.
At the last LeanTaaS Transform event in June, we joined with OR leaders from around the country to identify common myths and misconceptions about getting full use of the OR — and discussed solutions that truly remove the obstacles to full access, full visibility, and full utilization of resources, including time. For follow-up insights on these, see our Transform event in December 2021.
Myth 1: “Improvements in FCOTS (first case on time starts), Turnover, and Case Length Accuracy can create access for surgeons needing operating time.”
Why a myth? It is easy to become overly preoccupied with operating room efficiency metrics. Benchmarks are useful for tracking daily room flow and improving patient and surgeon satisfaction. Unless case times are especially short, however, these don’t allow for more cases on the schedule. Only minor efficiency gains can be made from improvements in FCOTS and turnover, not improvements in surgeon access to OR time.
The best practice: Focus on metrics like scheduled downtime, which does create more case capacity. Scheduled downtime accounts for about 50% of unused OR time. Engaging surgeons and stakeholders in the scheduling process, and building a collaborative culture across clinics and facilities, also helps support better distribution of case time. Meanwhile, efficiency metrics can be helpful in improving staff satisfaction and directing this culture change.
Myth 2: “Surgical Block Utilization is a strong metric to hold block owners accountable for how they use their block.”
Why a myth? The Surgical Block Utilization metric holds surgeons accountable for every single unused minute of time they leave on the table, including small blocks they cannot control. This is neither surgeon-centric nor actionable. It fails to account for complications or accurately compare across service lines. When decisions are made on this metric, blocks are often repurposed in the wrong amounts from the wrong surgeons on the wrong days.
The best practice: A metric that addresses block usage and promotes true accountability in opening truly reusable time. If OR leadership focuses instead on large chunks of unused block time that could be used for additional cases (i.e. Collectable Time), they can establish rules around time releases that reflect the reality of OR schedules.
Myth #3 “Auto release deadlines are effective for opening up block time surgeons don’t need.”
Why a myth? When auto release systems are set now, they are often not data driven. They tend not to account for details like variations in booking lead times across different service lines and surgeons. Deadlines tend instead to be set uniformly across all block owners, too close to dates of surgery to allow other surgeons to see, claim, and use the time. Auto release rarely creates access to any usable OR time.
The best practice: Data-driven auto release deadlines based on the surgeon or service’s unique patterns. These should account for booking lead time and be based on historical booking patterns. Different service lines have highly varied needs for time and urgency, so accurate information and reminders are crucial to getting buy-in from clinic staff who could easily see the impact of time released.
Myth #4 “We need more resources to increase access,” or “The robot room is always occupied, so we must need another robot.”
Why a myth? Surgical resources like the robot room are expensive, in high demand, and challenging to access. Most organizations provide “reserved access” to the robot(s) they have, though they want to treat it as first-come, first-served. This means no one really knows who is using the robot at what time, or if the robot room is in fact being used for a non-robotic case. In turn, “robot time” is only released very close to the date of surgery, and time is only accessible once blocks are auto released. As a result, there is not enough access to the robot to cover all cases that require it and organizations come to believe they must invest in an additional one.
The best practice: Better visibility into use of the existing robot and increased access. Employing surgical scheduling software that offers a visualizer, accurate lead time based on historic patterns, and accurate robotic availability may reveal that the existing robot or robots have capacity for additional cases to be completed. One hospital was able to accommodate an almost 30% increase in robot case minutes by using scheduling tools that could allocate robot time to surgeons who historically needed it most while leaving some available to be claimed on an open exchange.
Myth 5: “Our EHR gives us all we need to make meaningful decisions and optimize OR capacity.”
Why a myth? EHRs collect and present information that’s critical to managing care and operations. But they only have the power to present this information descriptively, showing what issues already exist or what happened in the past. These systems can’t function predictively, using past patterns of volume and usage to present likely outcomes, or prescriptively, to suggest best decisions for the future. Any advanced analytics must be requested specifically from the system by users who know specifically what to enter and look for.
The best practice: Adopting tools built on prescriptive and predictive data analytics. This serves relevant information to schedulers and surgeons clearly and up-front. These tools support immediate meaningful decisions that actively open up time and access for all. Functions like release reminders and proactive prescriptions on reusable time are driven by these high-level analytics, which are not readily available in EHRs.
For more information and case studies on analytics-driven surgical scheduling software, or to continue the conversation, see iQueue for Operating Rooms. To hear live from leaders of successfully managed ORs, register for December’s virtual Transform summit.