Operating Room Utilization Alone Is Not an Accurate Metric for the Allocation of Operating Room Block Time to Individual Surgeons with Low Caseloads

2003 ◽  
Vol 98 (5) ◽  
pp. 1243-1249 ◽  
Author(s):  
Srinivasa N. Raja ◽  
Franklin Dexter ◽  
Alex Macario ◽  
Rodney D. Traub ◽  
David A. Lubarsky

Introduction Many surgical suites allocate operating room (OR) block time to individual surgeons. If block time is allocated to services/groups and yet the same surgeon invariably operates on the same weekday, for all practical purposes block time is being allocated to individual surgeons. Organizational conflict occurs when a surgeon with a relatively low OR utilization has his or her allocated block time reduced. The authors studied potential limitations affecting whether a facility can accurately estimate the average block time utilizations of individual surgeons performing low volumes of cases. Methods Discrete-event computer simulation. Results Neither 3 months nor 1 yr of historical data were enough to be able to identify surgeons who had persistently low average OR utilizations. For example, with 3 months of data, the widths of the 95% CIs for average OR utilization exceeded 10% for surgeons who had average raw utilizations of 83% or less. If during a 3-month period a surgeon's measured adjusted utilization is 65%, there is a 95% chance that the surgeon's average adjusted utilization is as low as 38% or as high as 83%. If two surgeons have measured adjusted utilizations of 65% and 80%, respectively, there is a 16% chance that they have the same average adjusted utilization. Average OR utilization can be estimated more precisely for surgeons performing more cases each week. Conclusions Average OR utilization probably cannot be estimated precisely for low-volume surgeons based on 3 months or 1 yr of historical OR utilization data. The authors recommend that at surgical suites trying to allocate OR time to individual low-volume surgeons, OR allocations be based on criteria other than only OR utilization (e.g., based on OR efficiency).

2020 ◽  
Author(s):  
Juliane Neumann ◽  
Christine Angrick ◽  
Celina Höhn ◽  
Dirk Zajonz ◽  
Mohamed Ghanem ◽  
...  

Abstract Background: The design and internal layout of modern operating rooms (OR) are influencing the surgical team’s collaboration and communication, ergonomics, as well as intraoperative hygiene substantially. Yet, there is no objective method for the assessment and design of operating room setups for different surgical disciplines and intervention types available. The aim of this work is to establish an improved OR setup for common procedures in arthroplasty. Methods With the help of computer simulation, a method for the design and assessment of enhanced OR setups was developed. New OR setups were designed, analyzed in a computer simulation environment and evaluated in the actual intraoperative setting. Thereby, a 3D graphical simulation representation enabled the strong involvement of clinical stakeholders in all phases of the design and decision-making process of the new setup alternatives. Results The implementation of improved OR setups reduced the instrument handover time between the surgeon and the scrub nurse, the travel paths of the OR team as well as shortened the procedure duration. Additionally, the ergonomics of the OR staff were improved. Conclusion The developed simulation method was evaluated in the actual intraoperative setting and proved its benefit for the design and optimization of OR setups for different surgical intervention types. As a clinical result, enhanced setups for total knee arthroplasty and total hip arthroplasty surgeries were established in daily clinical routine and the OR efficiency was improved.


2020 ◽  
Author(s):  
Juliane Neumann ◽  
Christine Angrick ◽  
Celina Höhn ◽  
Dirk Zajonz ◽  
Mohamed Ghanem ◽  
...  

Abstract Background: The design and internal layout of modern operating rooms (OR) are influencing the surgical team’s collaboration and communication, ergonomics, as well as intraoperative hygiene substantially. Yet, there is no objective method for the assessment and design of operating room setups for different surgical disciplines and intervention types available. The aim of this work is to establish an improved OR setup for common procedures in arthroplasty. Methods With the help of computer simulation, a method for the design and assessment of enhanced OR setups was developed. New OR setups were designed, analyzed in a computer simulation environment and evaluated in the actual intraoperative setting. Thereby, a 3D graphical simulation representation enabled the strong involvement of clinical stakeholders in all phases of the design and decision-making process of the new setup alternatives. Results The implementation of improved OR setups reduced the instrument handover time between the surgeon and the scrub nurse, the travel paths of the OR team as well as shortened the procedure duration. Additionally, the ergonomics of the OR staff were improved. Conclusion The developed simulation method was evaluated in the actual intraoperative setting and proved its benefit for the design and optimization of OR setups for different surgical intervention types. As a clinical result, enhanced setups for total knee arthroplasty and total hip arthroplasty surgeries were established in daily clinical routine and the OR efficiency was improved.


Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 67
Author(s):  
Stefanie Hering ◽  
Nico Schäuble ◽  
Thomas M. Buck ◽  
Brigitta Loretz ◽  
Thomas Rillmann ◽  
...  

Increasing regulatory demands are forcing the pharmaceutical industry to invest its available resources carefully. This is especially challenging for small- and middle-sized companies. Computer simulation software like FlexSim allows one to explore variations in production processes without the need to interrupt the running process. Here, we applied a discrete-event simulation to two approved film-coated tablet production processes. The simulations were performed with FlexSim (FlexSim Deutschland—Ingenieurbüro für Simulationsdienstleistung Ralf Gruber, Kirchlengern, Germany). Process visualization was done using Cmap Tools (Florida Institute for Human and Machine Cognition, Pensacola, FL, USA), and statistical analysis used MiniTab® (Minitab GmbH, Munich, Germany). The most critical elements identified during model building were the model logic, operating schedule, and processing times. These factors were graphically and statistically verified. To optimize the utilization of employees, three different shift systems were simulated, thereby revealing the advantages of two-shift and one-and-a-half-shift systems compared to a one-shift system. Without the need to interrupt any currently running production processes, we found that changing the shift system could save 50–53% of the campaign duration and 9–14% of the labor costs. In summary, we demonstrated that FlexSim, which is mainly used in logistics, can also be advantageously implemented for modeling and optimizing pharmaceutical production processes.


2020 ◽  
Author(s):  
Yiruo Lu ◽  
Yongpei Guan ◽  
Jennifer Fishe ◽  
Thanh Hogan ◽  
Xiang Zhong

Abstract Health care systems are at the frontline to fight the COVID-19 pandemic. An emergent question for each hospital is how many general ward and intensive care unit beds are needed and how much personal protective equipment to be purchased. However, hospital pandemic preparedness has been hampered by a lack of sufficiently specific planning guidelines. In this paper, we developed a computer simulation approach to evaluating bed utilizations and the corresponding supply needs based on the operational considerations and constraints in individual hospitals. We built a data-driven SEIR model which is adaptive to control policies and can be utilized for regional forecast targeting a specific hospital’s catchment area. The forecast model was integrated into a discrete-event simulation which modeled the patient flow and the interaction with hospital resources. We tested the simulation model outputs against patient census data from UF Health Jacksonville, Jacksonville, FL. Simulation results were consistent with the observation that the hospital has ample bed resources to accommodate the regional COVID patients. After validation, the model was used to predict future bed utilizations given a spectrum of possible scenarios to advise bed planning and stockpiling decisions. Lastly, how to optimally allocate hospital resources to achieve the goal of reducing the case fatality rate while helping a maximum number of patients to recover was discussed. This decision support tool is tailored to a given hospital setting of interest and is generalizable to other hospitals to tackle the pandemic planning challenge.


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