The Power Law in Operating Room Management

被引:0
作者
Timothy Wong
Erik J. Zhang
Andrea J. Elhajj
Donna M. Rizzo
Kevin A. Sexton
Jaideep J. Pandit
Mitchell H. Tsai
机构
[1] Johns Hopkins Medicine,Department of Anesthesiology and Critical Care Medicine
[2] University of Vermont Larner College of Medicine,College of Engineering and Mathematical Sciences
[3] University of Vermont,Department of Civil & Environmental Engineering
[4] University of Vermont,Department of Surgery
[5] University of Arkansas for Medical Sciences,Department of Anesthesiology, Department of Orthopaedics and Rehabilitation (By Courtesy), Department of Surgery (By Courtesy)
[6] Nuffield Department of Clinical Neurosciences,undefined
[7] University of Vermont Larner College of Medicine,undefined
来源
Journal of Medical Systems | 2021年 / 45卷
关键词
Power law; Complex adaptive systems; Perioperative services; Operating room management; acute care surgery; Inter-event times;
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学科分类号
摘要
The Acute Care Surgery model has been implemented by many hospitals in the United States. As complex adaptive systems, healthcare systems are composed of many interacting elements that respond to intrinsic and extrinsic inputs. Systems level analysis may reveal the underlying organizational structure of tactical block allocations like the Acute Care Surgery model. The purpose of this study is to demonstrate one method to identify a key characteristic of complex adaptive systems in the perioperative services. Start and end times for all surgeries performed at the University of Vermont Medical Center OR1 were extracted for two years prior to the transition to an Acute Care Surgery service and two years following the transition. Histograms were plotted for the inter-event times calculated from the difference between surgical cases. A power law distribution was fit to the post-transition histogram. The Kolmogorov–Smirnov test for goodness-of-fit at 95% level of significance shows the histogram plotted from post-transition inter-event times follows a power law distribution (K-S = 0.088, p = 0.068), indicating a Complex Adaptive System. Our analysis demonstrates that the strategic decision to create an Acute Care Surgery service has direct implications on tactical and operational processes in the perioperative services. Elements of complex adaptive systems can be represented by a power law distributions and similar methods may be applied to identify other processes that operate as complex adaptive systems in perioperative care. To make sustained improvements in the perioperative services, focus on manufacturing-based interventions such as Lean Six Sigma should instead be shifted towards the complex interventions that modify system-specific behaviors described by complex adaptive system principles when power law relationships are present.
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