Play #4 – Implementing Parallel Processing to Increase OR Efficiency
Operating rooms (ORs) are the primary revenue and profit contributor for most hospitals – similarly, they are one of the largest cost centers. The value of an OR minute is often marked at $100+ for a health system. Each OR minute requires valuable team member time from nursing, anesthesia, and surgeons, as well as capacity utilization of limited OR suites.
With fewer than 20% of hospitals hitting their cost targets[i], OR productivity and efficiency must be a high priority to stay competitive in today’s market. Yet, current efficiency efforts focus primarily on optimizing linear processes rather than seeking to increase productivity by completing tasks in parallel. Process improvement via step-by-step adjustments (linear improvement) has limited potential as compared to parallel improvement efforts which seek to disrupt linear processes and complete multiple steps simultaneously.
Implementing parallel processing in the OR generates the opportunity for significant productivity gains. There is the opportunity to move certain tasks outside of the OR to reduce procedure time (see the first two studies below), as well as the opportunity to better orchestrate the activity within the procedure (third study).
In the first study from 2006 at Massachusetts General Hospital of 66 patients, Friedman, Sokal, Berger, and Chang, used parallel processing to reduce procedure time on average by 9.6 min which cumulatively reduced block time utilization by 33%, enabling unused block time to be reallocated to other surgeons and procedural volume to increase. They accomplished this by placing arterial catheters, intravenous lines, and administering anesthesia in pre-op while the OR was being prepared, were able to significantly reduce block time utilization[ii]. At $100/OR minute (a cost per minute that is representative of many large hospital’s structure), a 9.6 min reduction in procedure time creates $960 of incremental profit per case and $480,000 in incremental value for a surgeon performing 500 procedures per year.
In the second study from 2006 at MetroHealth outside Cleveland, Harders, Malangoni, and Weight re-designed the OR processes using multiple tactics to realize an average reduction of 23 min per procedure, from 65 minutes to 42 minutes. Their tactics included: the use of modular tables in pre-op to speed patient transfer, attachment of monitoring devices in pre-op, re-assignment of the anesthesiologist to pre-op to cover the next patient as soon as the prior patient was extubated, retention of the circulator in the OR to set up for the next case instead of following patient to the PACU, and commencement of OR clean up as soon as wound was closed and dressed[iii].. Once again, at a notional cost of $100/OR min, this represents a $2,300 savings per procedure, and at 500 procedures a year, a $1.15 mm savings per doctor.
In the final study from 2008 at Beth Israel Deaconess of 150 patients, Lee reduced procedural time on average by 16% (8.2 to 6.9 hours for unilateral and 12.8 to 10.6 hours for bilateral reconstruction) and reduced operative costs by 5-12%[iv]. To accomplish this, he mapped the intra-operative process of deep inferior epigastric perforator flap breast reconstruction and instituted simultaneous flap harvest and resection (parallel processing). This procedural change resulted in an average reduction in procedural time of Time savings at 1.3 – 2.2 hours per procedure not only have profound advantages for patient outcomes, but also create enormous savings for the OR. At the notional value of $100/OR minute this time savings equates to $7,800 to $13,200 in savings.
Parallel processing efforts require a paradigm shift and require diligent effort by all members of the surgical team, as well as a more granular understanding of the intra-operative activities. Effort that is iterative and must be supported by new tools, and enabled with new data and analytics.
Our experience enabling procedural optimization and teamwork suggests that successful parallel processing efforts share three success factors which ExplORer enables.
- Comparative Data. Parallel processing efforts require time and cost data gathered before and after parallel processing is introduced, to enable benchmarking. Additionally, it’s important to include data on patient and surgical team member experience, satisfaction, as well as outcomes, whenever possible. Money and time savings that do not lead to improved outcomes and surgical experiences for all participants is antithetical to surgical improvement.
Figure 1) Scrub referencing their role-specific workflow intraoperatively, via a tablet in sterile sleeve
ExplORer can be used to collect procedural data, before and after parallel processes are introduced, or to A/B test linear and parallel operative processes on the same types of procedures. Data is collected seamlessly without disruption using our tablet based application, enabling you to create a longitudinal data set across an episode of care.
- Optimized Processes. Before launching parallel processing programs, it’s a wise idea to optimize those processes that are going to be performed in parallel so that they are as lean and well understood by staff as possible; doing so builds team confidence and reduces the temptation to add additional resources because of parallel processes.
Figure 2) As a procedure is performed, ExplORer tracks the stages and steps of the case and provides historical, real-time performance data and predictive analytics to attending surgeons, residents, and OR administrators to enhance the quality of care and efficiency.
With ExplORer, you can map out and test optimized workflows and introduce them into practice prior to moving over to parallel execution. Ensuring teammates are coordinated while working on different tasks simultaneously is critical to building team confidence and support.
- Shared Workflow and Vision. Teamwork is the cornerstone of successful surgeries. The voices and perspectives of all participants must be heard and present in the workflow and goals of the procedure. When this is accomplished, surgical team members fall into a routine, or flow, that elevates individual and collective performance and creates a meaningful sense of team unity.
Figure 3) ExplORer creates a shared, dynamic experience for surgical teams in which each role in the procedure is thoroughly mapped and communicated throughout each procedure (from left to right: scrub, circulator, surgeon). Each team member can follow the progression of a case and optimize their contribution, while staying aware of their teammate’s actions, and steps ahead of the surgeon.
If you are considering implementing parallel processes at any stage of the surgical process, we’d love to hear from you and have a conversation about your and our insights and perspective. Please contact us at email@example.com to set up a conversation.
[i] Strata Decision Technology Research, July 2014
[ii] Increasing Operating Room Efficiency Through Parallel Processing, Friedman, Sokal, Berger, Chang, Annals of Surgery, January, 2006
[iii] Harders M, Malangoni M A, Weight S, et al. Improving operating room efficiency through process redesign. Surgery. October 2006;140:509-516.
[iv] J Am Coll Surg. 2008 Dec;207(6):865-73. doi: 10.1016/j.jamcollsurg.2008.08.016. Epub 2008 Oct 10
Posted by Thomas G. Knight, Chief Operating Officer.
About ExplORer Surgical
ExplORer Surgical is an interactive surgical playbook that reduces disruptions and wasted disposables by improving surgical team communication. ExplORer Surgical also provides real-time performance and scheduling data to OR administrators to enhance the quality of care and efficiency. Surgical teams use the software to coordinate their activities while managing their tools and supplies in a way never before possible. The result is optimal teamwork, increased efficiency, and high performance.